Digital Commons Network^™

Integration Of Agile Development In Standard Labs, Felix Huening, Cindy Mund

Practice Papers

In addition to the technical content, modern courses at university should also teach professional skills to enhance the competencies of students towards their future work. The competency driven approach including technical as well as professional skills makes it necessary to find a suitable way for the integration into the corresponding module in a scalable and flexible manner. Agile development, for example, is essential for the development of modern systems and applications and makes use of dedicated professional skills of the team members, like structured group dynamics and communication, to enable the fast and reliable development. This paper presents an easy …

Multicultural Online Collaborative Learning: Students’ Engagement In Design Thinking Framework, Shizuyo Asai, Yuli Rahmawati, Fauzan Khairi Che Harun, Tula Jutarosaga

Practice Papers

This paper presents a collaborative learning course in which students from four universities in different Asian countries work in mixed teams to learn how to develop user-centered products and solve problems in a hands-on way using the Design Thinking framework. For the past three years, the courses were conducted entirely online. Cooperation and collaboration among diverse people from different backgrounds are essential to solving the social problems facing the world today. Like many universities, we have been actively sending our students abroad to provide opportunities to experience diverse cultures and values, but the pandemic has made it very difficult to …

Bridgewater Magazine, Volume 33, Number 2, Fall 2023, Bridgewater State University

Bridgewater Magazine

Taking Flight: Meet BSU students and alumni from the growing Aviation Science Program. Also in this issue: Two faculty members research the lives and times of early Black and Indigenous local citizens; Faculty researchers recount details of two of the enslaved in Colonial Bridgewater; and Alumna finds career satisfaction in helping others.

Data-Driven Strategies For Pain Management In Patients With Sickle Cell Disease, Swati Padhee

Browse all Theses and Dissertations

This research explores data-driven AI techniques to extract insights from relevant medical data for pain management in patients with Sickle Cell Disease (SCD). SCD is an inherited red blood cell disorder that can cause a multitude of complications throughout an individual’s life. Most patients with SCD experience repeated, unpredictable episodes of severe pain. Arguably, the most challenging aspect of treating pain episodes in SCD is assessing and interpreting the patient’s pain intensity level due to the subjective nature of pain. In this study, we leverage multiple data-driven AI techniques to improve pain management in patients with SCD. The proposed approaches …

Emotions In Engineering Education (Chapter 8), James L. Huff Ph.D., Johanna Lonngren, Ines Dirieto, Roland Tormey

Faculty Research and Publications

Contrary to common stereotypes, engineering education and practice are not purely rational activities. Emotions, just like cognition, play important roles in teaching, learning, and professional practice. Today, there is a nascent body of research exploring emotions in engineering education (EEE). However, much of the existing research does not adequately theorize emotions, and the range of theories and methods used is still relatively narrow. With this chapter, we hope to inspire more investigators to conduct EEE research and to explore currently underutilized theories, methods, and research foci. This chapter introduces the reader to the multidisciplinary field of emotion research, then focus …

Advancing An Integrative Perspective Of Identity In Engineering Education (Chapter 9), James L. Huff Ph.D., Monique S. Ross Ph.D.

Faculty Research and Publications

Existing research has used identity as a theoretical construct to help us understand a wide array of phenomena, such as engagement and persistence in engineering. By understanding the personal, social, and sociocultural forces that operate in the developmental processes of an individual, we understand how they come to make sense of who they are. Further, we come to learn how they position themselves in relation to what it means to be an engineer. However, identity research in engineering education has supported a diffuse set of theoretical perspectives that do not organically coalesce. This chapter advances an integrated conceptualization of engineering …

Revised Avenues Of Assessment In Higher Education In The Presence Of Ai Generative Contents, Muhammad Iqbal

HECA Research Conference

This study explores the impact of Generative Artificial Intelligence (AI) tools on academic assessments, focusing on their efficacy in generating unique content across various domains. Dr. Muhammad Iqbal from CCT College Dublin emphasizes the increasing prevalence of AI generative tools and their potential influence on learning quality in academia. The study addresses concerns related to assessment standards in higher education and proposes the evaluation of AI-generated content reliability.

Graphical User Interface For Evidential Reasoning Models, Rohin Gopalakrishnan

Master's Projects

The Capri system is an evidential reasoning system based on the belief function calculus to support automated reasoning and decision making in uncertain environments. Example domains of application include, medical diagnosis, as well as identifying biological biomarkers. The purpose of this project is to build a Python web-based and app-based Graphical User Interface (GUI), called PyGrapher, that facilitates building graphical evidential reasoning models. The graphical models built using PyGrapher will then be converted to a form that is suitable for input to the Capri system. The PyGrapher system provides an intuitive means to build and manipulate evidential reasoning models as …

Improving Communication Procedures By Means Of Videorecorded Proposals, Marta Aguilar, Jordi Olivella

Practice Papers

There is an agreement regarding the importance of communication in the promotion processes of all types of technical or entrepreneurial initiatives. Communication skills have to make it possible to obtain the maximum interaction with the agents involved and facilitate the commitment of these agents to a project. In this context, communicators’ erroneous perception of their own abilities and of how they are transmitting the information is a significant drawback that calls for improvement. Video-recording someone when speaking creates an impact on them given that the possibility of seeing themselves implies a significant change in the learning process. This technique has …

Exploring The Impact Of Problem-Based Learning On Student Learning Outcomes: Findings From The Pbl South Asia Project, Andrius Jurelionis, Gintare Stankeviciute, Avinash Dhital, Ellen Van Andel, Julia Sundman, Laura Stasiuliene, Shakuntala Acharya, Riina Subra

Practice Papers

This paper presents the results of surveys conducted among students and teachers / mentors in Nepal, Bhutan, and India, regarding the impact of implementing Problembased learning (PBL) methodology in engineering and multidisciplinary projects. The surveys were carried out under the Erasmus+ funded project, "Strengthening Problembased learning in South Asian Universities" (PBL South Asia). The project aimed to address the issues of education quality, employability, and sustainable development in the region by enhancing students’ practical experience, communication skills, teamwork abilities, as well as academic knowledge through PBL-adapted courses. As a result, South Asian higher education institutions have implemented PBL courses in …

Binary Text Classification Using Genetic Programming With Crossover-Based Oversampling For Imbalanced Datasets, Mona Aljero, Nazi̇fe Di̇mi̇li̇ler

Turkish Journal of Electrical Engineering and Computer Sciences

It is well known that classifiers trained using imbalanced datasets usually have a bias toward the majority class. In this context, classification models can present a high classification performance overall and for the majority class, even when the performance for the minority class is significantly lower. This paper presents a genetic programming (GP) model with a crossover-based oversampling technique for oversampling the imbalanced dataset for binary text classification. The aim of this study is to apply an oversampling technique to solve the imbalanced issue and improve the performance of the GP model that employed the proposed technique. The proposed technique …

Lvq Treatment For Zero-Shot Learning, Firat İsmai̇loğlu

Turkish Journal of Electrical Engineering and Computer Sciences

In image classification, there are no labeled training instances for some classes, which are therefore called unseen classes or test classes. To classify these classes, zero-shot learning (ZSL) was developed, which typically attempts to learn a mapping from the (visual) feature space to the semantic space in which the classes are represented by a list of semantically meaningful attributes. However, the fact that this mapping is learned without using instances of the test classes affects the performance of ZSL, which is known as the domain shift problem. In this study, we propose to apply the learning vector quantization (LVQ) algorithm …

Acm Web Conference 2023, Usha Lokala, Kaushik Roy, Utkarshani Jaimini, Amit Sheth

Publications

Improving the performance and explanations of ML algorithms is a priority for adoption by humans in the real world. In critical domains such as healthcare, such technology has significant potential to reduce the burden on humans and considerably reduce manual assessments by providing quality assistance at scale. In today’s data-driven world, artificial intelligence (AI) systems are still experiencing issues with bias, explainability, and human-like reasoning and interpretability. Causal AI is the technique that can reason and make human-like choices making it possible to go beyond narrow Machine learning-based techniques and can be integrated into human decision-making. It also offers intrinsic …

Advancing Internet Viewpoint Diversity: A Novel Algorithm And A Corpus Creation Tool, Jeffrey Harwell

CGU Theses & Dissertations

A fundamental requirement for Western democracy is an informed and engaged electorate with access to a wide range of viewpoints. However, concerns have arisen regarding how information technology affects the diversity of viewpoints available. In response to an increasingly polarized society and worries surrounding filter bubbles and algorithmic bias, this research presents a novel tool for constructing internet-based topical corpora and an algorithm tailored for viewpoint detection and the curation of diverse search results.Following a comprehensive exploration of viewpoint diversity through the lenses of mass media, social psychology, and information retrieval, this dissertation presents an approach to operationalize viewpoint diversity …

Solar Power Plant Location Selection Problem By Using Electre-Iii Method In Pythagorean Neutrosophic Programming Approach (A Case Study On Green Energy In India), Florentin Smarandache, Rajesh Kumar Saini, Ashik Ahirwar Ahirwa

Branch Mathematics and Statistics Faculty and Staff Publications

India dropped its target of generating 500 GW of renewable energy capacity from non responsibilities to ations Framework Convention on reducing carbon Abstract: India dropped its target of 500 GW of renewable energy capacity fossil fuel sources by 2030. Its responsibilities the United Nations Framework Conven Climate Change [UNFCCC],and reducing radiations by one billion tonnes by the end of the decade at the COP26 conference, held in Glasgow in November 2022.Researchers are continually searching for inexhaustible and reasonable energy sources. Solar energy is one of the greenest sources of energy and is also one of the cleanest. The most important …

Evaluation Of Different Machine Learning, Deep Learning And Text Processing Techniques For Hate Speech Detection, Nabil Shawkat

Graduate Theses/Dissertations

Social media has become a domain that involves a lot of hate speech. Some users feel entitled to engage in abusive conversations by sending abusive messages, tweets, or photos to other users. It is critical to detect hate speech and prevent innocent users from becoming victims. In this study, I explore the effectiveness and performance of various machine learning methods employing text processing techniques to create a robust system for hate speech identification. I assess the performance of Naïve Bayes, Support Vector Machines, Decision Trees, Random Forests, Logistic Regression, and K Nearest Neighbors using three distinct datasets sourced from social …

Discovering Child Sexual Abuse Material Creators’ Behaviors And Preferences On The Dark Web, Vuong Ngo, Rahul Gajula, Christina Thorpe, Susan Mckeever

Articles

Background: Producing, distributing or discussing child sexual abuse materials (CSAM) is often committed through the dark web in order to remain hidden from search engines and regular users. Additionally, on the dark web, the CSAM creators employ various techniques to avoid detection and conceal their activities. The large volume of CSAM on the dark web presents a global social problem and poses a significant challenge for helplines, hotlines and law enforcement agencies.

Objective: Identifying CSAM discussions on the dark web and uncovering associated metadata insights into characteristics, behaviours and motivation of CSAM creators.

Participants and Setting: We have conducted an …

Toward Inclusive Online Environments: Counterfactual-Inspired Xai For Detecting And Interpreting Hateful And Offensive Tweets, Muhammad Deedahwar Mazhar Qureshi, Muhammad Atif Qureshi, Wael Rashwan

Articles

The prevalence of hate speech and offensive language on social media platforms such as Twitter has significant consequences, ranging from psychological harm to the polarization of societies. Consequently, social media companies have implemented content moderation measures to curb harmful or discriminatory language. However, a lack of consistency and transparency hinders their ability to achieve desired outcomes. This article evaluates various ML models, including an ensemble, Explainable Boosting Machine (EBM), and Linear Support Vector Classifier (SVC), on a public dataset of 24,792 tweets by T. Davidson, categorizing tweets into three classes: hate, offensive, and neither. The top-performing model achieves a weighted …

An Entropy-Based Risk Index (Eri) Of Mining Health And Safety Using Clustering And Statistical Methods, Dharmasai Eshwar Reddy Sirigiri

Dissertations, Master's Theses and Master's Reports

Over the last decade, the mining industry has seen a significant reduction in the number of fatalities in the United States. However, the annual employee hours have also decreased during the same period. Therefore, it is crucial to evaluate the historical mining data and identify the potential risks of a mine through the mine risk index. The risk indicators also describe the severity of accidents and injuries at mine sites. The variables such as citation, order, significant & substantial citations, lost time, and no lost time injuries and penalties are considered for the determination of the risk index. However, using …

Evaluation Of Text Transformers For Classifying Sentiment Of Reviews By Using Tf-Idf, Bert (Word Embedding), Sbert (Sentence Embedding) With Support Vector Machine Evaluation, Mina Jamshidian

Dissertations

As the online world evolves and new media emerge, consumers are sharing their reviews and opinions online. This has been studied in various academic fields, including marketing and computer science. Sentiment analysis, a technique used to identify the sentiment of a piece of text, has been researched in different domains such as movie reviews and mobile app ratings. However, the video game industry has received relatively little research on experiential products. The purpose of this study is to apply sentiment analysis to user reviews of games on Steam, a popular gaming platform, in order to produce actionable results. The video …

Modelling And Mitigating Interlocutor Confusion In Situated Human-Avatar And Human-Robot Interaction, Na Li

Dissertations

Human-Robot Interaction (HRI) is an important but challenging field focused on improving the interaction between humans and robots, to make the interaction more intelligent and effective. However, building a natural conversational HRI is an interdisciplinary challenge for scholars, engineers, and designers. Achieving successful conversational interaction with a social robot necessitates not only observing a user’s active participation in the interaction but also being aware of their emotional and attitudinal states as the interaction progresses. On the topic of attitudinal states, one field that has received little attention to date is monitoring the user for possible confusion states. Confusion is a …

A Structured Narrative Prompt For Prompting Narratives From Large Language Models: Sentiment Assessment Of Chatgpt-Generated Narratives And Real Tweets, Christopher J. Lynch, Erik J. Jensen, Virginia Zamponi, Kevin O'Brien, Erika Frydenlund, Ross Gore

VMASC Publications

Large language models (LLMs) excel in providing natural language responses that sound authoritative, reflect knowledge of the context area, and can present from a range of varied perspectives. Agent-based models and simulations consist of simulated agents that interact within a simulated environment to explore societal, social, and ethical, among other, problems. Simulated agents generate large volumes of data and discerning useful and relevant content is an onerous task. LLMs can help in communicating agents' perspectives on key life events by providing natural language narratives. However, these narratives should be factual, transparent, and reproducible. Therefore, we present a structured narrative prompt …

Machine Learning Models To Automate Radiotherapy Structure Name Standardization, Priyankar Bose

Theses and Dissertations

Structure name standardization is a critical problem in Radiotherapy planning systems to correctly identify the various Organs-at-Risk, Planning Target Volumes and `Other' organs for monitoring present and future medications. Physicians often label anatomical structure sets in Digital Imaging and Communications in Medicine (DICOM) images with nonstandard random names. Hence, the standardization of these names for the Organs at Risk (OARs), Planning Target Volumes (PTVs), and `Other' organs is a vital problem. Prior works considered traditional machine learning approaches on structure sets with moderate success. We compare both traditional methods and deep neural network-based approaches on the multimodal vision-language prostate cancer …

Demo Alleviate: Demonstrating Artificial Intelligence Enabled Virtual Assistance For Telehealth: The Mental Health Case, Kaushik Roy, Vedant Khandelwal, Raxit Goswami, Nathan Dolbir, Jinendra Malekar, Amit Sheth

Publications

After the pandemic, artificial intelligence (AI) powered support for mental health care has become increasingly important. The breadth and complexity of significant challenges required to provide adequate care involve: (a) Personalized patient understanding, (b) Safety-constrained and medically validated chatbot patient interactions, and (c) Support for continued feedback-based refinements in design using chatbot-patient interactions. We propose Alleviate, a chatbot designed to assist patients suffering from mental health challenges with personalized care and assist clinicians with understanding their patients better. Alleviate draws from an array of publicly available clinically valid mental-health texts and databases, allowing Alleviate to make medically sound and informed …

Impact Of Character N-Grams Attention Scores For English And Russian News Articles Authorship Attribution, Liliya Mukhmutova, Robert J. Ross, Giancarlo Salton

Conference papers

Language embeddings are often used as black-box word-level tools that provide powerful language analysis across many tasks, but yet for many tasks such as Authorship Attribution access to feature level information on character n-grams can provide insights to help with model refinement and development. In this paper we investigate and evaluate the importance of character n-grams within an embeddings context in authorship attribution through the use of attention scores. We perform this investigation both for English (Reuters_50_50) and Russian (Taiga) news authorship datasets. Our analysis show that character n-grams attention score is higher for n-grams that are considered to be …

Automatic Presentation Slide Generation Using Llms, Tanya Gupta

Master's Theses

Presentation slides are widely used for conveying information in academic and professional contexts. However, manual slide creation can be time-consuming. Our research focuses on automated slide generation, specifically for scientific research papers. Automating the creation of presentation slides for scientific documents is a rather novel task and hence, there’s limited training data available and there also exists the token constraints of language models like BERT, with a maximum sequence length of 512 tokens. In this study, we fine-tune large language models, including Longformer-Encoder-Decoder (supporting sequences up to 16,834 tokens) and BIGBIRD-Pegasus (supporting sequences up to 4,096 tokens). We tackle this …

The Encyclopedia Of Neutrosophic Researchers, Vol. 6, Florentin Smarandache, Maikel Yelandi Leyva Vázquez, Jesús Estupiñán Ricardo

Branch Mathematics and Statistics Faculty and Staff Publications

Este es el Sexto volumen de la Enciclopedia de Investigadores Neutróficos, editados a partir de materiales ofrecidos por los autores que respondieron a la invitación del editor. Los autores se enumeran alfabéticamente. La introducción contiene una breve historia de la neutrosófica, y en especial se sus impacto en latinoamérica junto con enlaces a los principales artículos y libros. Conjunto neutrosófico, lógica neutrosófica, probabilidad neutrosófica, estadística neutrosófica, medida neutrosófica, precálculo neutrosófico, cálculo neutrosófico, psicología neutrosófica, sociología neutrosófica etc., están ganando una atención significativa en resolver muchos problemas de la vida real que implican incertidumbre, imprecisión, vaguedad, incompletitud, inconsistencia e indeterminación. En …

Prediction Of 2024 Indian Pm Election Results Using Sentiment Analysis On Twitter Data, Surabhi Gupta

Master's Projects

This sentiments analysis study presents a methodical approach to predict the 2024 Indian Prime Minister Election. Data collected spanning from 2020 to 2023 from Twitter using hashtags such as IndianPMElection2024 and on topics such as the revocation of the special status of Jammu and Kashmir, the Farm Bill, and the Digital India initiative, form the core of this research. We utilized a combination of sentiment extraction tools-namely, the NLP Town's Bidirectional Encoder Representations from Transformers (BERT)-based multilingual uncased sentiment model, Valance Aware Dictionary for Sentiment Reasoning (VADER), and TextBlob. Additionally, we used a well-established machine learning model Naive Bayes, deep …

Unlocking The Pragmatics Of Emoji: Evaluation Of The Integration Of Pragmatic Markers For Sarcasm Detection, Niamh Farnham

ICT

Emojis have become an integral element of online communications, serving as a powerful, under-utilised resource for enhancing pragmatic understanding in NLP. Previous works have highlighted their potential for improvement of more complex tasks such as the identification of figurative literary devices including sarcasm due to their role in conveying tone within text. However present state-of-the-art does not include the consideration of emoji or adequately address sarcastic markers such as sentiment incongruence. This work aims to integrate these concepts to generate more robust solutions for sarcasm detection leveraging enhanced pragmatic features from both emoji and text tokens. This was achieved by …

Data-Driven Strategies For Disease Management In Patients Admitted For Heart Failure, Ankita Agarwal

Browse all Theses and Dissertations

Heart failure is a syndrome which effects a patient’s quality of life adversely. It can be caused by different underlying conditions or abnormalities and involves both cardiovascular and non-cardiovascular comorbidities. Heart failure cannot be cured but a patient’s quality of life can be improved by effective treatment through medicines and surgery, and lifestyle management. As effective treatment of heart failure incurs cost for the patients and resource allocation for the hospitals, predicting length of stay of these patients during each hospitalization becomes important. Heart failure can be classified into two types: left sided heart failure and right sided heart failure. …