Digital Commons Network^™

Translating Natural Language Queries To Sparql, Shreya Satish Bhajikhaye

Master's Projects

The Semantic Web is an extensive knowledge base that contains facts in the form of RDF
triples. These facts are not easily accessible to the average user because to use them requires
an understanding of ontologies and a query language like SPARQL. Question answering systems
form a layer of abstraction on linked data to overcome these issues. These systems allow the
user to input a question in a natural language and receive the equivalent SPARQL query. The
user can then execute the query on the database to fetch the desired results. The standard
techniques involved in translating natural language questions …

Automating Text Encapsulation Using Deep Learning, Anket Sah

Master's Projects

Data is an important aspect in any form be it communication, reviews, news articles, social media data, machine or real-time data. With the emergence of Covid-19, a pandemic seen like no other in recent times, information is being poured in from all directions on the internet. At times it is overwhelming to determine which data to read and follow. Another crucial aspect is separating factual data from distorted data that is being circulated widely. The title or short description of this data can play a key role. Many times, these descriptions can deceive a user with unwanted information. The user …

Analyzing Empirical Quality Metrics Of Deep Learning Models For Antimicrobial Resistance, Huy H. Nguyen, Sanjay Pillay, Allison Roderick, Hao Wang, John Santerre

SMU Data Science Review

Antimicrobial Resistance (AMR) is a growing concern in the medical field. Over-prescription of antibiotics as well as bacterial mutations have caused some once lifesaving drugs to become ineffective against bacteria. However, the problem of AMR might be addressed using Machine Learning (ML) thanks to increased availability of genomic data and large computing resources. The Pathosystems Resource Integration Center (PATRIC) has genomic data of various bacterial genera with sample isolates that are either resistant or susceptible to certain antibiotics. Past research has used this database to use ML algorithms to model AMR with successful results, including accuracies over 80%. To better …

Is Gallaudet Diverse? Creating An R Package To Measure Institutional Diversity, Emelia Beldon

Undergraduate University Honors Capstones

One of the biggest trends in social science is the study of racial and ethnic diversity measures. Numerous scholarly articles and journals detail how important it is to encourage a racially and ethnically diverse community in higher education. However, the question remains: how do we accurately measure racial and ethnic diversity? Furthermore, how do we present the diversity in terms of statistics for best use? With this project, I answer these questions. I created an R software package, diversityGV, to measure institutional racial and ethnic diversity using the Generalized Variance mathematical approach. I then used diversityGV with a dataset from …

Automated Analysis Of Rfps Using Natural Language Processing (Nlp) For The Technology Domain, Sterling Beason, William Hinton, Yousri A. Salamah, Jordan Salsman

SMU Data Science Review

Much progress has been made in text analysis, specifically within the statistical domain of Term Frequency (TF) and Inverse Document Frequency (IDF). However, there is much room for improvement especially within the area of discovering Emerging Trends. Emerging Trend Detection Systems (ETDS) depend on ingesting a collection of textual data and TF/IDF to identify new or up-trending topics within the Corpus. However, the tremendous rate of change and the amount of digital information presents a challenge that makes it almost impossible for a human expert to spot emerging trends without relying on an automated ETD system. Since the U.S. Government …

Intangible Cultural Heritage: A Benefit To Climate-Displaced And Host Communities, Gül Aktürk, Martha B. Lerski

Publications and Research

Climate change is borderless, and its impacts are not shared equally by all communities. It causes an imbalance between people by creating a more desirable living environment for some societies while erasing settlements and shelters of some others. Due to floods, sea level rise, destructive storms, drought, and slow-onset factors such as salinization of water and soil, people lose their lands, homes, and natural resources. Catastrophic events force people to move voluntarily or involuntarily. The relocation of communities is a debatable climate adaptation measure which requires utmost care with human rights, ethics, and psychological well-being of individuals upon the issues …

Analyses And Creation Of Author Stylized Text, Keith Carlson

Dartmouth College Ph.D Dissertations

Written text is one of the major ways that humans communicate their thoughts. A single thought can be expressed through many different combinations of words, and the writer must choose which they will use. We call the idea which is communicated the content of the message, and the particular words chosen to express the content, the style. The same content expressed in a different style may tell something useful about the author of the text (e.g., the author's identity), may be easier to understand for different audiences, or may evoke different emotions in the reader.

In this work we explore …

Fine-Grained Sentiment Analysis For Customer Review, Bing Han, Meng Han, Jing (Selena) He

Master of Science in Computer Science Theses

Natural Language Processing (NLP) is one of the most attractive technologies in many applications in real-life. Sentiment analysis, which has devoted to know others' think or feel about an experience or an item and hence take an action, is one of the most developed area in both academia and industry. Among sentiment analysis, fine-grained aspect sentiment analysis attempts to analyze emotional attitude categorized into different aspects or features of an(a) experience/service/product. Although aspect level sentiment analysis could provide more useful information, the proposed models' performance were relative poor compared with document-level or sentence-level sentiment analysis due to the lack of …

Pharyngeal Constriction As A Cause For Late Acquisition And Speech Sound Disorders Of Rhotic Sounds In English, Spanish, And French, Connor Mahon

The Downtown Review: An Interdisciplinary Journal Written and Peer-Reviewed by Mandel Honors College Students at Cleveland State University

This paper attempts to explain why rhotic sounds are cross-linguistically late developing among the sound inventory of children. Included is a summary of the current literature regarding classification of rhotic sounds, an examination of the articulatory movement of the tongue root, and an overview of the clinical implications on the field of speech-language pathology. The evidence presented supports the hypothesis that pharyngeal constriction is characteristic of rhotic sounds in many languages, and that it is related to the relative late acquisition and higher rate of speech sound disorders, as seen in English, Spanish, and French.

Machine Learning In Stock Price Prediction Using Long Short-Term Memory Networks And Gradient Boosted Decision Trees, Carl Samuel Cederborg

Honors Projects

Quantitative analysis has been a staple of the financial world and investing for many years. Recently, machine learning has been applied to this field with varying levels of success. In this paper, two different methods of machine learning (ML) are applied to predicting stock prices. The first utilizes deep learning and Long Short-Term Memory networks (LSTMs), and the second uses ensemble learning in the form of gradient tree boosting. Using closing price as the training data and Root Mean Squared Error (RMSE) as the error metric, experimental results suggest the gradient boosting approach is more viable.

Honors Symposium: ML is …

Game-Based Learning In Science: Can Video Games Simplify Organic Chemistry?, Rachel Israel

Senior Honors Theses

Organic chemistry has been taught in the same way for decades, and students still have difficulty understanding and comprehending the subject material. Perhaps it is time to change the methods by which this subject is taught. Video games have been successfully used in education to create learning environments that increase student motivation and engagement as well as challenge students and promote collaboration. It is difficult for students to maintain a growth mindset in organic chemistry within the classroom. However across different genres, video games create a unique environment where an individual is encouraged to try again when they fail. This …

Using Large Pre-Trained Language Models To Track Emotions Of Cancer Patients On Twitter, Will Baker

Computer Science and Computer Engineering Undergraduate Honors Theses

Twitter is a microblogging website where any user can publicly release a message, called a tweet, expressing their feelings about current events or their own lives. This candid, unfiltered feedback is valuable in the spaces of healthcare and public health communications, where it may be difficult for cancer patients to divulge personal information to healthcare teams, and randomly selected patients may decline participation in surveys about their experiences. In this thesis, BERTweet, a state-of-the-art natural language processing (NLP) model, was used to predict sentiment and emotion labels for cancer-related tweets collected in 2019 and 2020. In longitudinal plots, trends in …

Why Chomsky Normal Form: A Pedagogical Note, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

To simplify the design of compilers, Noam Chomsky proposed to first transform a description of a programming language -- which is usually given in the form of a context-free grammar -- into a simplified "normal" form. A natural question is: why this specific normal form? In this paper, we provide an answer to this question.

Five Revolutionary Ideas In The 1950s-70s Science: 90th Birthday Of Revolt Pimenov, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

This year, Revolt Pimenov, a philosophical thinker whose main ideas were in geometry of space-time, would have turned 90. In this essay, we explain how in the 1950s-70s, when he was most productive, his were two of the five natural and important revolutionary scientific ideas -- along with fuzzy logic, constructive mathematics, and scalar-tensor theory of gravitation, ideas that, in our opinions, still have potential to change the world.

Using Sentiment And Emotion Analysis Of News Articles To Analyze The Effects Of Leader’S Statements On Covid-19 Spread, Poojitha Thota

Computer Science and Engineering Theses - Archive

Leaders generally include government officials, politicians, etc. Their statements can highly affect people’s decisions in many ways. Currently, in the pandemic situation, many statements were being passed every hour and day, which showed an impact on the spread of corona virus cases at certain location. So, this paper proposes a supervised model to analyze the variations of COVID-19 data based upon the leader’s statements passed at certain time and location. The proposed methodology consists of sentiment and emotion analysis for the leader’s statements to determine the true intentions of the leader. The leader’s statements are a collection of data obtained …

Toward A More Holistic Worldview: Environmental Values In Context, Erica Lynne Walters

Undergraduate Honors Thesis Collection

This study extensively examines the formation of pro-environmental behaviors as mediated by the Value-Belief-Norm (VBN) Theory. Using this theoretical framework, qualitative, in-depth interviews were conducted with a small number of Butler University students (n=10). The findings of the data collection demonstrate the limitations of the VBN Theory when applied to pro-environmental behavior. Data analysis demonstrates the role that formative experiences, environmental education, and connectedness to nature can play as intervening influences in the linear translation posited by the VBN Theory. Moreover, the confluence of various values that emerged among research participants suggests the need for a more holistic value orientation …

Detecting Bots Using A Hybrid Approach, Edmund Kofi Genfi

Theses, Dissertations and Culminating Projects

Artificial intelligence (AI) remains a crucial aspect for improving our modern lives but it also casts several social and ethical issues. One issue is of major concern, investigated in this research, is the amount of content users consume that is being generated by a form of AI known as bots (automated software programs). With the rise of social bots and the spread of fake news more research is required to understand how much content generated by bots is being consumed. This research investigates the amount of bot generated content relating to COVID-19. While research continues to uncover the extent to …

Plprepare: A Grammar Checker For Challenging Cases, Jacob Hoyos

Electronic Theses and Dissertations

This study investigates one of the Polish language’s most arbitrary cases: the genitive masculine inanimate singular. It collects and ranks several guidelines to help language learners discern its proper usage and also introduces a framework to provide detailed feedback regarding arbitrary cases. The study tests this framework by implementing and evaluating a hybrid grammar checker called PLPrepare. PLPrepare performs similarly to other grammar checkers and is able to detect genitive case usages and provide feedback based on a number of error classifications.

Zariski Geometries And Quantum Mechanics, Milan Zanussi

Boise State University Theses and Dissertations

Model theory is the study of mathematical structures in terms of the logical relationships they define between their constituent objects. The logical relationships defined by these structures can be used to define topologies on the underlying sets. These topological structures will serve as a generalization of the notion of the Zariski topology from classical algebraic geometry. We will adapt properties and theorems from classical algebraic geometry to our topological structure setting. We will isolate a specific class of structures, called Zariski geometries, and demonstrate the main classification theorem of such structures. We will construct some Zariski structures where the classification …

Distant Stars Become Future Homes: The Close Relationship Of Interstellar Between Hard Science-Fiction And Spectacle, Gabriel Davis

Undergraduate Honors Theses

Hard Science-fiction shares a close relationship with the element of spectacle. This is especially apparent in Christopher Nolan’s Interstellar (2014), a film based in realistic science and emotional appeal. Nolan makes use of creating a team comprised of creative minds with different backgrounds. This includes theoretical physicist Kip Thorne, co-writer Jonathan Nolan, and composer Hans Zimmer. Together, the four develop a film that focuses on three main facets of science: time dilation, black holes, and dimensions. Incorporating these elements based in the historical world gives Interstellar its classification as hard science-fiction, a genre based more solidly in realistic science than …

Automatically Selecting Follow-Up Questions For Deficient Bug Reports, Mia Mohammad Imran, Agnieszka Ciborowska, Kostadin Damevski

Computer Science Faculty Research & Creative Works

The availability of quality information in bug reports that are created daily by software users is key to rapidly fixing software faults. Improving incomplete or deficient bug reports, which are numerous in many popular and actively developed open-source software projects, can make software maintenance more effective and improve software quality. In this paper, we propose a system that addresses the problem of bug report incompleteness by automatically posing follow-up questions, intended to elicit answers that add value and provide missing information to a bug report. Our system is based on selecting follow-up questions from a large corpus of already posted …

Factors That Influence Teachers' Utilization Of Siop Learning Strategies When Teaching English Language Learners, Courtney R. Stuart

Theses and Dissertations

Despite standardized certification tests and popular English Language Learner trainings, the strategies and methods used in two educators’ classes would not be identical. In this case-study we look to see what variables cause teachers to utilize certain strategies and how these variables affect the number of strategies used consistently when teaching ELLs. We study the effect of teachers’ language experiences, certifications, participation in SIOP trainings, education levels, perceived preparedness, and years spent in the classroom.

Using quantitative and qualitative data we conclude that dual-language fluency and professional advancements can lead to teachers using more ELL learning strategies in their classrooms, …

Cortical Dynamics Of Language, Kiefer Forseth

Dissertations and Theses (Open Access)

The human capability for fluent speech profoundly directs inter-personal communication and, by extension, self-expression. Language is lost in millions of people each year due to trauma, stroke, neurodegeneration, and neoplasms with devastating impact to social interaction and quality of life. The following investigations were designed to elucidate the neurobiological foundation of speech production, building towards a universal cognitive model of language in the brain. Understanding the dynamical mechanisms supporting cortical network behavior will significantly advance the understanding of how both focal and disconnection injuries yield neurological deficits, informing the development of therapeutic approaches.

Kinetics For Enzymatic Conversion Of Biomass To Glucose, Jordan Broadwater

Undergraduate Honors Theses

Biofuels are a sought-after alternative for fossil fuels in today’s society. More specifically, cellulose-based biofuel is an avenue of research intending to limit waste and provide new renewable energy. Cellulose is a rigid polymer of glucose monomers that is found abundantly across different agriculture crops. However, its stability is a barrier to energy production from this source. Pretreatment followed by hydrolysis of cellulosic materials serves a potential to produce glucose to be used in biofuels in larger quantities compared to other methods. This project studied the effect microwave pretreatment and oxygenation have on hydrolysis of cellulose in Arundo Donax. Arundo …

Factors That Affect E-Learning Platforms After The Spread Of Covid-19: Post Acceptance Study, Rana Saeed Al-Maroof, Khadija Alhumaid, Iman Akour, Said Salloum

All Works

The fear of vaccines has led to population rejection due to various reasons. Students have had their own inquiries towards the effectiveness of the vaccination, which leads to vaccination hesitancy. Vaccination hesitancy can affect students' perception, hence, acceptance of e-learning platforms. Therefore, this research attempts to explore the post-acceptance of e-learning platforms based on a conceptual model that has various variables. Each variable contributes differently to the post-acceptance of the e-learning platform. The research investigates the moderating role of vaccination fear on the post-acceptance of e-learning platforms among students. Thus, the study aims at exploring students' perceptions about their post-acceptance …

Retrieval-Augmented Generation For Code Summarization Via Hybrid Gnn, Shangqing Liu, Yu Chen, Xiaofei Xie, Jingkai Siow, Yang Liu

Research Collection School Of Computing and Information Systems

Source code summarization aims to generate natural language summaries from structured code snippets for better understanding code functionalities. However, automatic code summarization is challenging due to the complexity of the source code and the language gap between the source code and natural language summaries. Most previous approaches either rely on retrieval-based (which can take advantage of similar examples seen from the retrieval database, but have low generalization performance) or generation-based methods (which have better generalization performance, but cannot take advantage of similar examples). This paper proposes a novel retrieval-augmented mechanism to combine the benefits of both worlds. Furthermore, to mitigate …

Dialogue State Tracking With Incremental Reasoning, Lizi Liao, Le Hong Long, Yunshan Ma, Wenqiang Lei, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Tracking dialogue states to better interpret user goals and feed downstream policy learning is a bottleneck in dialogue management. Common practice has been to treat it as a problem of classifying dialogue content into a set of pre-defined slot-value pairs, or generating values for different slots given the dialogue history. Both have limitations on considering dependencies that occur on dialogues, and are lacking of reasoning capabilities. This paper proposes to track dialogue states gradually with reasoning over dialogue turns with the help of the back-end data. Empirical results demonstrate that our method outperforms the state-of-theart methods in terms of joint …

Characterising The Knowledge About Primitive Variables In Java Code Comments, Mahfouth Alghamdi, Shinpei Hayashi, Takashi Kobayashi, Christoph Treude

Research Collection School Of Computing and Information Systems

Primitive types are fundamental components available in any programming language, which serve as the building blocks of data manipulation. Understanding the role of these types in source code is essential to write software. Little work has been conducted on how often these variables are documented in code comments and what types of knowledge the comments provide about variables of primitive types. In this paper, we present an approach for detecting primitive variables and their description in comments using lexical matching and advanced matching. We evaluate our approaches by comparing the lexical and advanced matching performance in terms of recall, precision, …

Angrybert: Joint Learning Target And Emotion For Hate Speech Detection, Md Rabiul Awal, Rui Cao, Roy Ka-Wei Lee, Sandra Mitrović

Research Collection School Of Computing and Information Systems

Automated hate speech detection in social media is a challenging task that has recently gained significant traction in the data mining and Natural Language Processing community. However, most of the existing methods adopt a supervised approach that depended heavily on the annotated hate speech datasets, which are imbalanced and often lack training samples for hateful content. This paper addresses the research gaps by proposing a novel multitask learning-based model, AngryBERT, which jointly learns hate speech detection with sentiment classification and target identification as secondary relevant tasks. We conduct extensive experiments to augment three commonly-used hate speech detection datasets. Our experiment …

2021- The Twenty-Fifth Annual Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the Twenty-fifth Annual Symposium of Student Scholars, held on April 29, 2021. Includes abstracts from the presentations and posters.