Digital Commons Network^™

Ethics Of Emerging Communication And Collaboration Technologies For Children, Juan Pablo Hourcade, Elizabeth Bonsignore, Tamara Clegg, Flannery Currin, Jerry A. Fails, Georgie Qiao Jin, Summer R. Schmuecker, Lana Yarosh

Computer Science Faculty Publications and Presentations

This SIG will provide child-computer interaction researchers and practitioners, as well as other interested CSCW attendees, an opportunity to discuss topics related to the ethics of emerging communication and collaboration technologies for children. The child-computer interaction community has conducted many discussions on ethical issues, including a recent SIG at CHI 2023. However, the angle of communication and collaboration has not been a focus, even though emerging technologies could affect these aspects in significant ways. Hence, there is a need to consider emerging technologies, such as extended reality, and how they may impact the way children communicate and collaborate in face-to-face, …

Towards 6g: Key Technological Directions, Chamitha De Alwis, Pardeep Kumar, Quoc-Viet Pham, Kapal Dev, Ashuman Kalla, Madhusanka Lianage, Woo-Joo Hwang

Department of Mathematics Publications

Sixth-generation mobile networks (6G) are expected to reach extreme communication capabilities to realize emerging applications demanded by the future society. This paper focuses on six technological directions towards 6G, namely, intent-based networking, THz communication, artificial intelligence, distributed ledger technology/blockchain, smart devices and gadget-free communication, and quantum communication. These technologies will enable 6G to be more capable of catering to the demands of future network services and applications. Each of these technologies is discussed highlighting recent developments, applicability in 6G, and deployment challenges. It is envisaged that this work will facilitate 6G related research and developments, especially along the six technological …

A Machine Learning Approach To Deepfake Detection, Delaney Conrad

All Undergraduate Theses and Capstone Projects

The ability to manipulate videos has been around for decades but a process that once would take time, money, and professionals, can now be created by anyone due to the rapid advancement of deepfake technology. Deepfakes use deep learning artificial intelligence to make fake digital content, typically in the form of swapping a person’s face in a video or image. This technology could easily threaten and manipulate individuals, corporations, and political organizations, so it is essential to find methods for detecting deepfakes. As the technology for creating deepfakes continues to improve, these manipulated videos are becoming increasingly undetectable. It is …

Optimizing Deep Neural Networks Performance: Efficient Techniques For Training And Inference, Ankit Sharma

Graduate Thesis and Dissertation 2023-2024

Recent advances in computer vision tasks are mainly due to the success of large deep neural networks. The current state-of-the-art models have high computational costs during inference and suffer from a high memory footprint. Therefore, deploying these large networks on edge devices remains a serious concern. Furthermore, training these over-parameterized networks is computationally expensive and requires a longer training time. Thus, there is a demand to develop techniques that can efficiently reduce training costs and also be able to deploy neural networks on mobile and embedded devices. This dissertation presents practices like designing a lightweight network architecture and increasing network …

Covid-19 Crowd Detection, Mustafa Ibrahim, Aly M. Zeineldin, Yameen Khan, Ayman Elmesalami, Soad Ibrahim

OUR Journal: ODU Undergraduate Research Journal

Object detection was introduced by researchers for face detection. Researchers explain how the detected face is divided into minor frames to be recognized by the algorithm. Due to COVID-19 and government regulations, many people face problems going to shopping centers and shop safely. It has been very hard for both the government and the people to manage social distancing. In our study, we developed a system using Raspberry Pi-4 that will detect the distance between people along with counting the number of distance and mask violations. An error message will appear on the screen in red, showing the total number …

Multimodal Learning: Generating Precise Chest X-Ray Report On Thorax Abnormality, Gaurab Subedi

Dissertations and Theses

Chronic respiratory diseases, ranking as the third leading cause of death worldwide according to the 2017 World Health Organization (WHO) report, affect a staggering 544.9 million individuals. Compounding this public health challenge is the fact that over 80% of health systems grapple with shortages in their radiology departments, highlighting an urgent need for accessible and efficient diagnostic solutions. While various image classification models for analyzing thorax abnormalities have been developed, relying solely on one type of dataset (image data, for example) for thorax abnormality analysis is insufficient. Integrating texts with image data could provide more accuracy as well as analysis. …

Multimodal Learning: Generating Precise Chest X-Ray Report On Thorax Abnormality, Gaurab Subedi

Dissertations and Theses

Chronic respiratory diseases, ranking as the third leading cause of death worldwide according to the 2017 World Health Organization (WHO) report, affect a staggering 544.9 million individuals. Compounding this public health challenge is the fact that over 80% of health systems grapple with shortages in their radiology departments, highlighting an urgent need for accessible and efficient diagnostic solutions. While various image classification models for analyzing thorax abnormalities have been developed, relying solely on one type of dataset (image data, for example) for thorax abnormality analysis is insufficient. Integrating texts with image data could provide more accuracy as well as analysis. …

Comprehensive Cough Data Analysis On Coda Tb, Jyoti Yadav, Aparna S. Varde, Lei Xie

School of Computing Faculty Scholarship and Creative Works

This work leverages CODA TB, a groundbreaking dataset for a novel comprehensive method of early TB detection from medical big data. Departing from the erstwhile, we find mere cough duration less effective in TB prediction. We discover key demographic and clinical factors (e.g. heart rate, presenting symptoms) to be crucial in distinguishing TB cases, motivating comprehensive cough data analysis with enhanced screening.

Bringing Stakeholders Along For The Ride: Towards Supporting Intentional Decisions In Software Evolution: Supplemental Material, Alicia M. Grubb, Paola Spoletini

Data

Supplemental material for the research paper entitled, "Bringing Stakeholders Along for the Ride: Towards Supporting Intentional Decisions in Software Evolution". This paper presents an initial literature review to define intentionality, disambiguate it from its use in literature, and position it in relation to similar concepts. This supplement contains the literature review data file.

Multimodal Emotion Analysis With Focused Attention, Siddhi Kiran Bajracharya

Dissertations and Theses

Emotion analysis, a subset of sentiment analysis, involves the study of a wide array of emotional indicators. In contrast to sentiment analysis, which restricts its focus to positive and negative sentiments, emotion analysis extends beyond these limitations to a diverse spectrum of emotional cues. Contemporary trends in emotion analysis lean toward multimodal approaches that leverage audiovisual and text modalities. However, implementing multimodal strategies introduces its own set of challenges, marked by a rise in model complexity and an expansion of parameters, thereby creating a need for a larger volume of data. This thesis responds to this challenge by proposing a …

Application Of Genomic Compression Techniques For Efficient Storage Of Captured Network Traffic Packets, James Alfred Loving

CCAC Theses and Dissertations

In cybersecurity, one of most important forensic tools are audit files; they contain a record of cyber events that occur on systems throughout the enterprise. Threats to an enterprise have become one of the top concerns of IT professionals world-wide. Although there are various approaches to detect anomalous insider behavior, these approaches are not always able to detect advanced persistent threats or even exfiltration of sensitive data by insiders. The issue is the volume of network data required to identify this anomalous activity. It has been estimated that an average corporate user creates a minimum of 1.5 MB audit data …

Multimodal Game-Based Learning In Post-Secondary Education, Nathan A. Vanos

EWU Masters Thesis Collection

In this age of unprecedented technological proliferation, educators have been given a unique opportunity to enhance classroom engagement. That opportunity is multimodal game-based learning (MGBL): classroom instruction through a combination of games and multiple modalities of information. Using today’s 3D systems and virtual reality tools, this concept can be explored to depths never before possible. The aim of this project was to design and implement an application that could be used to evaluate how MGBL could impact student engagement and learning, specifically at the post-secondary level. The application implemented during this work was a 3D and virtual reality Simulator for …

A Comparative Assessment Of Human Factors In Cybersecurity: Implications For Cyber Governance, Muhammad Umair Shah, Farkhund Iqbal, Umair Rehman, Patrick C.K. Hung

All Works

This paper provides an extensive overview of cybersecurity awareness in the young, educated, and technology-savvy population of the United Arab Emirates (UAE), compared to the United States of America (USA) for advancing the scholarship and practice of global cyber governance. We conducted comparative empirical studies to identify differences in specific human factors that affect cybersecurity behaviour in the UAE and the USA. In addition, we employed several control variables to observe reliable results. We used Hofstede’s theoretical framework on culture to advance our investigation. The results show that the targeted population in the UAE exhibits contrasting interpretations of cybersecurity awareness …

Mapping The Focal Points Of Wordpress: A Software And Critical Code Analysis, Bryce Jackson

Electronic Theses and Dissertations, 2020-2023

Programming languages or code can be examined through numerous analytical lenses. This project is a critical analysis of WordPress, a prevalent web content management system, applying four modes of inquiry. The project draws on theoretical perspectives and areas of study in media, software, platforms, code, language, and power structures. The applied research is based on Critical Code Studies, an interdisciplinary field of study that holds the potential as a theoretical lens and methodological toolkit to understand computational code beyond its function. The project begins with a critical code analysis of WordPress, examining its origins and source code and mapping selected …

Identification And Modeling Social Media Influence Pathways: A Characterization Of A Disinformation Campaign Using The Flooding-The-Zone Strategy Via Transfer Entropy, Jasser Jasser

Electronic Theses and Dissertations, 2020-2023

The internet has made it easy for narratives to spread quickly and widely without regard for accuracy or the harm they may cause to society. Unfortunately, this has led to the rise of bad actors who use fake and misleading articles to spread harmful misinformation. These actors flood the information space with low-quality articles in an effort to disrupt opposing narratives, sow confusion, and discourage the pursuit of truth. In societies that prioritize free speech, maintaining control over the information space remains a persistent challenge. Achieving this requires strategic planning to protect the dissemination of information in ways that promote …

“Any Means Necessary To Refuse Erasure By Algorithm:” Lillian-Yvonne Bertram’S Travesty Generator, Zach Whalen

Communication & Digital Studies Articles

Lillian-Yvonne Bertram's 2019 book of poetry is titled Travesty Generator in reference to Hugh Kenner and Joseph O'Rourke's Pascal program to “fabricate pseudo-text” by producing text such that each n-length string of characters in the output occurs at the same frequency as in the source text. Whereas for Kenner and O'Rourke, labeling their work a “travesty” is a hyperbolic tease or a literary burlesque, for Bertram, the travesty is the political reality of racism in America. For each of the works Travesty Generator, Bertram uses the generators of computer poetry to critique, resist, and replace narratives of oppression and to …

A Data Delivery Mechanism For Disconnected Mobile Applications, Shashank Hegde

Master's Projects

Previous attempts to bring the data of the internet to environments that do not have continuous connectivity to the internet have made use of special hardware which requires additional expenditure on installation. We will develop a software-based infrastructure running on existing Android smartphones to exchange application data between a disconnected user’s phone and corresponding application servers on the internet. The goal of this project is to implement client and server modules for this infrastructure to run on a disconnected phone and the internet respectively. These modules will multiplex application data to be sent into packages and distribute the data present …

Vehicle-Based Disconnected Data Distribution, Aditya Singhania

Master's Projects

The world today is highly connected and there is an immense dependency on this connectivity to accomplish basic everyday tasks. However much of the world lacks connectivity. Even in well-connected locations, natural disasters can cause infrastructure disruption. To combat these situations, Delay Tolerant Networks

(DTNs) employ to store and forward techniques along with intermittently connected transports to provide data connectivity. DTNs focus on intermittently connected networks however what if the regions are never connected? For example, Region A - is never connected to the internet, and Region B – has internet connectivity. Using a vehicle that travels between the two …

Personalized Tweet Recommendation Using Users’ Image Preferences, Shashwat Avinash Kadam

Master's Projects

In the era of information explosion, the vast amount of data on social media platforms can overwhelm users. Not only does this information explosion contain irrelevant content, but also intentionally fabricated articles and images. As a result, personalized recommendation systems have become increasingly important to help users navigate and make sense of this data. We propose a novel technique to use users’ image preferences to recommend tweets. We extract vital information by analyzing images liked by users and use it to recommend tweets from Twitter. As many images online have no descriptive metadata associated with them, in this framework, we …

Graph Deep Learning Based Hashtag Recommender For Reels On Social Media, Sriya Balineni

Master's Projects

Many businesses, including Facebook, Netflix, and YouTube, rely heavily on a recommendation system. Recommendation systems are algorithms that attempt to provide consumers with relevant suggestions for items such as movies, videos, or reels (microvideos) to watch, hashtags for their posts, songs to listen to, and products to purchase. In many businesses, recommender systems are essential because they can generate enormous amounts of revenue and make the platform stand out when compared to others. Reels are a feature of the social media platforms that enable users to create and share videos of up to sixty seconds in length. Individuals, businesses, and …

Influence Maximization Based On Community Detection And Dominating Sets, Ameya Marathe

Master's Projects

An online platform where various people come together to share information and communicate is called a social network. These platforms are set apart from other means of communication mostly because you can follow and interact also with different people even some you never met, comment on their posts, and re-sharing their posts. Companies such as Amazon and Walmart use these platforms daily for marketing purposes, like spreading information regarding new products and services they offer. They carefully select a subset of users, called influencers, who are usually the ones with high influence over the rest of the users. Influencers receive …

Image Captioning Using Reinforcement Learning, Venkat Teja Golamaru

Master's Projects

Image captioning is a crucial technology with numerous applications, including enhancing accessibility for the visually impaired, developing automated image indexing and retrieval systems, and enriching social media experiences. However, accurately describing the content of an image in natural language remains a challenge, particularly in low-resource settings where data and computational power are limited. The most advanced image captioning architectures currently use encoder-decoder structures that incorporate a sequential recurrent prediction model. This study adopts a typical Convolutional Neural Network (CNN) encoder Recurrent Neural Network (RNN) decoder structure for image captioning, but it has framed the problem as a sequential decision-making task. …

Application Of Knowledge Graph Techniques On Textbooks, Yutong Yao

Master's Projects

Textbooks are written and organized in a way that facilitates learning and understanding. Sections like glossary terms at the end of a textbook provide guidance on the topic of interest. However, it takes manual effort to create the index terms in the glossary that highlight the key referenced terminologies and related terms. Knowledge graphs, which have been used to represent and even reason over data and knowledge, can potentially capture textbook’s important terms, concepts, and their relations. Popular since the initial introduction by Google Knowledge Graphs (KGs), they combine graph and data to capture and model enormous amounts of relational …

A Novel Efficient Deep Learning Framework For Facial Inpainting - Face Reconstruction From Masked Images, Akshay Ravi

Master's Projects

The use of face masks due to the covid-19 pandemic has made surveillance of people very difficult. Since a mask covers most of the facial components, security cameras are rendered of little to no use in the identification of criminals. In order to realize what a face looks like behind a mask, we have to construct the facial features in the masked region. On a higher level, this falls under the field of image inpainting, i.e. filling missing regions of images or correcting irregularities in images. Current research on image inpainting shows promising results on images that have missing/incorrect patches …

Comparative Analysis Of Transformer-Based Models For Text-To-Speech Normalization, Pankti Dholakia

Master's Projects

Text-to-Speech (TTS) normalization is an essential component of natural language processing (NLP) that plays a crucial role in the production of natural-sounding synthesized speech. However, there are limitations to the TTS normalization procedure. Lengthy input sequences and variations in spoken language can present difficulties. The motivation behind this research is to address the challenges associated with TTS normalization by evaluating and comparing the performance of various models. The aim is to determine their effectiveness in handling language variations. The models include LSTM-GRU, Transformer, GCN-Transformer, GCNN-Transformer, Reformer, and a BERT language model that has been pre-trained. The research evaluates the performance …

Rideshare Using Degrees Of Separation: A Social Network-Based Approach, Gokul Garikipati

Master's Projects

Conventional ride-sharing services, such as Lyft and Uber, routinely match drivers with riders based on their proximity to each other, using GPS coordinates and mapping technology. The application then calculates the cost of the ride based on factors such as distance traveled and time spent in the car. The concept of six degrees of separation suggests that a maximum of 6 steps or relationships can connect any two individuals in the world. This idea could be applied to a ride-share service to provide a more personalized and efficient experience for users. Instead of just matching riders with drivers based on …

Nft Artifact Prediction Using Machine Learning, Rishabh Pandey

Master's Projects

NFT Prediction Systems are web applications that provide their users with valuable insights about the artifact. These insights are useful for investors and collectors to make better decisions about their purchases. This project builds upon the same concept of prediction by developing a web application to dynamically provide recommendations based on user input and training an ML model to predict their cost. Preliminary work for the prediction system involved data collection, pre-processing, analysis, and filtering of large datasets from diverse sources. The project focused on the development of a user- friendly UI to enable seamless categorization of search results generated …

Wikipedia Web Table Interpretation, Keyword-Based Search, And Ranking, Kartikee Dabir

Master's Projects

Information retrieval and data interpretation on the web, for the purpose of gaining knowledgeable insights, has been a widely researched topic from the onset of the world wide web or what is today popularly known as the internet. Web tables are structured tabular data present amidst unstructured, heterogenous data on the web. This makes web tables a rich source of information for a variety of tasks like data analysis, data interpretation, and information retrieval pertaining to extracting knowledge from information present on the web. Wikipedia tables which are a subset of web tables hold a huge amount of useful data, …

The New Student: The Enhancement Of An Ebook To Support Emotional Connection, Rebecca Zumaeta

Master's Projects

EBooks are a form of multimedia applications that encourage cognitive learning. Multimedia can also influence readers to have a deeper connection to the story. Understanding the influence of a static picture book versus an animated and audio guided eBook can prove valuable in developing learning media and other forms of content. In this research we take a published children's book and apply the content into a multimedia eBook. The purpose of the creation of the eBook is to compare the interest of a reader on a story when static format, when some multimedia is added and when the story is …

Detecting Botnets Using Hidden Markov Model, Profile Hidden Markov Model And Network Flow Analysis, Rucha Mannikar

Master's Projects

Botnet is a network of infected computer systems called bots managed remotely by an attacker using bot controllers. Using distributed systems, botnets can be used for large-scale cyber attacks to execute unauthorized actions on the targeted system like phishing, distributed denial of service (DDoS), data theft, and crashing of servers. Common internet protocols used by normal systems for regular communication like hypertext transfer (HTTP) and internet relay chat (IRC) are also used by botnets. Thus, distinguishing botnet activity from normal activity can be challenging. To address this issue, this project proposes an approach to detect botnets using peculiar traits in …