Digital Commons Network^™

Machine-Learning Approach To Automated Doubt Identification On Stack Overflow Comments To Guide Programming Learners, Tianhao Chen, Eng Lieh Ouh, Kar Way Tan, Siaw Ling Lo

Research Collection School Of Computing and Information Systems

Stack Overflow is a popular Q&A platform for developers to find solutions to programming problems. However, due to the varying quality of user-generated answers, there is a need for ways to help users find high-quality answers. While Stack Overflow's community-based approach can be effective, important technical aspects of the answer need to be captured, and users’ comments might contain doubts regarding these aspects. In this paper, we showed the feasibility of using a machine learning model to identify doubts and conducted data analysis. We found that highly reputed users tend to raise more doubts; most answers have doubt in the …

An Efficient Hybrid Genetic Algorithm For The Quadratic Traveling Salesman Problem, Quang Anh Pham, Hoong Chuin Lau, Minh Hoang Ha, Lam Vu

Research Collection School Of Computing and Information Systems

The traveling salesman problem (TSP) is the most well-known problem in combinatorial optimization which hasbeen studied for many decades. This paper focuses on dealing with one of the most difficult TSP variants named thequadratic traveling salesman problem (QTSP) that has numerous planning applications in robotics and bioinformatics.The goal of QTSP is similar to TSP which finds a cycle visiting all nodes exactly once with minimum total costs. However, the costs in QTSP are associated with three vertices traversed in succession (instead of two like in TSP). This leadsto a quadratic objective function that is much harder to solve.To efficiently solve …

Is Web3 Better Than Web2 For Investors? Evidence From Domain Name Auctions, Ping Fan Ke, Yi Meng Lau, Daniel Varghese Hanley

Research Collection School Of Computing and Information Systems

Blockchain-based assets are commonly believed to attract new investors. To investigate this claim, we compared investor preferences for Web2 and Web3 domain name auctions by analyzing daily auction patterns in Namecheap and OpenSea. Our results indicate that Web3 platforms may attract extreme investors with low or high values as a niche market. We found a significantly higher number of bids per auction, higher average bid prices, and greater price spreads on OpenSea, but a significantly lower number of unique bidders per auction. Our findings highlight the importance of considering the auction platform's characteristics and asset context when evaluating bid patterns …

Marketing In Metaverse: Sales-Avatar Visual Features On Customer Trust, Yuxin Liu, Keng Siau

Research Collection School Of Computing and Information Systems

The metaverse wave is sweeping across the world. Virtual shopping promises a bright future and has the potential to provide customers with an immersive and realistic shopping experience anytime and anywhere. Salesavatars are critical in customer trust development in virtual shopping in the metaverse by directly interacting with customers. Considering the virtual characteristics of the metaverse and the anonymity of salesavatars, this research investigates the effect of salesavatars' genders and ages on customers' trust in the metaverse through the lens of first impression formation. Two dimensions of facial first impression, perceived facial trustworthiness and perceived facial dominance, will be studied …

Peerda: Data Augmentation Via Modeling Peer Relation For Span Identification Tasks, Weiwen Xu, Xin Li, Yang Deng, Wai Lam, Lidong Bing

Research Collection School Of Computing and Information Systems

Span identification aims at identifying specific text spans from text input and classifying them into pre-defined categories. Different from previous works that merely leverage the Subordinate (SUB) relation (i.e. if a span is an instance of a certain category) to train models, this paper for the first time explores the Peer (PR) relation, which indicates that two spans are instances of the same category and share similar features. Specifically, a novel Peer Data Augmentation (PeerDA) approach is proposed which employs span pairs with the PR relation as the augmentation data for training. PeerDA has two unique advantages: (1) There are …

Goal Awareness For Conversational Ai: Proactivity, Non-Collaborativity, And Beyond, Yang Deng, Wenqiang Lei, Minlie Huang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Conversational systems are envisioned to provide social support or functional service to human users via natural language interactions. Conventional conversation researches mainly focus on the responseability of the system, such as dialogue context understanding and response generation, but overlooks the design of an essential property in intelligent conversations, i.e., goal awareness. The awareness of goals means the state of not only being responsive to the users but also aware of the target conversational goal and capable of leading the conversation towards the goal, which is a significant step towards higher-level intelligence and artificial consciousness. It can not only largely improve …

Augmenting Fake Content Detection In Online Platforms: A Domain Adaptive Transfer Learning Via Adversarial Training Approach, Ka Chung Ng, Ping Fan Ke, Mike K. P. So, Kar Yan Tam

Research Collection School Of Computing and Information Systems

Online platforms are experimenting with interventions such as content screening to moderate the effects of fake, biased, and incensing content. Yet, online platforms face an operational challenge in implementing machine learning algorithms for managing online content due to the labeling problem, where labeled data used for model training are limited and costly to obtain. To address this issue, we propose a domain adaptive transfer learning via adversarial training approach to augment fake content detection with collective human intelligence. We first start with a source domain dataset containing deceptive and trustworthy general news constructed from a large collection of labeled news …

Lightweight And Effective Website Fingerprinting Over Encrypted Dns, Yong Shao, Kenneth Hernandez, Kia Yang, Eric Chan-Tin, Mohammed Abuhamad

Computer Science: Faculty Publications and Other Works

The DNS over HTTPS (DoH) protocol is implemented to improve the original DNS protocol that uses unencrypted DNS queries and responses. With the DNS traffic, an eavesdropper can easily identify websites that a user is visiting. In order to address this concern of web privacy, encryption is used by performing a DNS lookup over HTTPS. In this paper, we studied whether the encrypted DoH traffic could be exploited to identify websites that a user has visited. This is a different type of website fingerprinting by analyzing encrypted DNS network traffic rather than the network traffic between the client and the …

Webtracker: Real Webbrowsing Behaviors, Daisy Reyes, Eno Dynowski, Taryn Chovan, John Mikos, Eric Chan-Tin, Mohammed Abuhamad, Shelia Kennison

Computer Science: Faculty Publications and Other Works

With increased privacy concerns, anonymity tools such as VPNs and Tor have become popular. However, the packet metadata such as the packet size and number of packets can still be observed by an adversary. This is commonly known as fingerprinting and website fingerprinting attacks have received a lot of attention recently as a known victim’s website visits can be accurately predicted, deanonymizing that victim’s web usage. Most of the previous work have been performed in laboratory settings and have made two assumptions: 1) a victim visits one website at a time, and 2) the whole website visit with all the …

Economic Value Of User Interface Design, Anna Kruse

Honors Program: Senior Projects (Public)

The economic value of well-designed user interfaces (UI) and user experiences (UX) is challenging to quantify, a topic that the current literature does not sufficiently explore. Those responsible for deciding whether to invest resources in UI/UX typically base these decisions on monetary considerations. The link between effective UI/UX design and profit may not be immediately clear to most, yet it is universally acknowledged that satisfied customers lead to successful business. To underscore the importance of investing in UI/UX, it is crucial to define the relationship between effective design and economic success in a way that can be understood by designers, …

Harnessing Artificial Intelligence For Early And Evolution Of Alzheimer’S Disease Detections And Enhancing Senior Mental Health Through Innovative Art-Singing Therapies: A Multidisciplinary Approach, Jocelyne Kiss, Geoffreyjen Edwards, Rachel Bouserhal, Elaine Champagne, Thierry Belleguic, Valéry Psyché, Charles Batcho, Carol Hudon, Sylsvie Ratté, Ingrid Verdruyckt, Marie-Hélène Parizeau, Aaron Liu-Rosenbaum, James Hudson, Marie-Louise Bourbeau, Marie Lemieux, Annik Charbonneau

Faculty Scholarship

The well-documented therapeutic potential of group singing for patients living with Alzheimer’s disease (PLAD) has been hindered by COVID-19 restrictions, exacerbating loneliness and cognitive decline among seniors in residential and long-term care centers (CHSLDs). Addressing this challenge, the multidisciplinary study aims to develop a patient-oriented virtual reality (XR) interaction system facilitating group singing for mental health support during confinement and enhancing the understanding of the links between Alzheimer’s disease, social interaction, and singing. The researchers also propose to establish an early AD detection system using voice, facial, and non-invasive biometric measurements and validate the efficacy of selected intervention practices. The …

2023 Chairs’ Welcome, Daniel Moreira, Aparna Bharati, Cecilia Pasquini, Yassine Yousfi

Computer Science: Faculty Publications and Other Works

Welcome to the 11th edition of the ACM Workshop on Information Hiding and Multimedia Security (IH&MMSec ‘23). This year’s workshop continues the tradition of representing one of the prime events in information hiding and multimedia security, attracting researchers and practitioners worldwide. Carrying on with the efforts of the previous edition to overcome the Pandemics and reunite the IH&MMSec community to present and discuss their work, this year’s meeting is held fully in person at the Water Tower Campus of Loyola University Chicago, located right at the heart of the Windy City. Bathed by the fresh waters of Lake Michigan, Chicago …

Adversarial Alignment For Source Free Object Detection, Qiaosong Chu, Shuyan Li, Guangyi Chen, Kai Li, Xiu Li

Machine Learning Faculty Publications

Source-free object detection (SFOD) aims to transfer a detector pre-trained on a label-rich source domain to an unlabeled target domain without seeing source data. While most existing SFOD methods generate pseudo labels via a source-pretrained model to guide training, these pseudo labels usually contain high noises due to heavy domain discrepancy. In order to obtain better pseudo supervisions, we divide the target domain into source-similar and source-dissimilar parts and align them in the feature space by adversarial learning. Specifically, we design a detection variance-based criterion to divide the target domain. This criterion is motivated by a finding that larger detection …

An Empirical Investigation Of Network Topology On Majority Illusion, Behavior Adoption, And Polarization, Sreeja Sreekantan Nair

USF Tampa Graduate Theses and Dissertations

Social influence plays a significant role in shaping opinions and behaviors both online and inthe physical world. The ways in which we interact with others and the information we receive can significantly influence our beliefs and attitudes towards different issues. While online social media provide platforms for such interactions, the underlying network structure can impact various social influence phenomena, including majority illusion, behavior adoption, and polarization.

This dissertation examines the role of network topology in three social influence processes:majority illusion, behavior adoption, and polarization. The majority illusion refers to a perception bias that occurs when individuals believe that an opinion …

The Use Of Artificial Intelligence In Higher Education: A Study On Faculty Perspectives In Universities In Egypt, Farah S. Sharawy

Theses and Dissertations

Artificial Intelligence (AI) is an emerging technology that is transforming various aspects of society, including higher education. This paper examines faculty perspectives from five different institutions; The American University in Cairo (AUC), The German University in Cairo (GUC), The Arab Academy for Science and Technology (AAST), Ain Shams University, and Cairo University, on the use of AI in higher education in teaching and learning in Egypt, with all its challenges and resources available to support it, and how it can be used to achieve equity and accessibility. This research was conducted through a qualitative study using semi-structured one- on-one interviews …

Numerical Simulation Of The Korteweg–De Vries Equation With Machine Learning, Kristina O. F. Williams, Benjamin F. Akers

Faculty Publications

A machine learning procedure is proposed to create numerical schemes for solutions of nonlinear wave equations on coarse grids. This method trains stencil weights of a discretization of the equation, with the truncation error of the scheme as the objective function for training. The method uses centered finite differences to initialize the optimization routine and a second-order implicit-explicit time solver as a framework. Symmetry conditions are enforced on the learned operator to ensure a stable method. The procedure is applied to the Korteweg–de Vries equation. It is observed to be more accurate than finite difference or spectral methods on coarse …

Trend Observation: Analysis On Development Trend Of Precision Medicine

Bulletin of Chinese Academy of Sciences (Chinese Version)

No abstract provided.

Agris: Wind-Adaptive Wideband Reconfigurable Intelligent Surfaces For Resilient Wireless Agricultural Networks At Millimeter-Wave Spectrum, Shuai Nie, M. C. Vuran

School of Computing: Faculty Publications

Wireless networks in agricultural environments are unique in many ways. Recent measurements reveal that the dynamics of crop growth impact wireless propagation channels with a long-term seasonal pattern. Additionally, short-term environmental factors, such as strong wind, result in variations in channel statistics. Next-generation agricultural fields, populated by autonomous tractors, drones, and high-throughput sensing systems, require high-throughput connectivity infrastructure, resulting in the future deployment of high-frequency networks, where they have not been deployed before. More specifically, when millimeter-wave (mmWave) communication systems, a viable candidate for 5G and 6G high-throughput solutions, are deployed for higher throughput, these issues become more prominent due …

The Power Of (Virtual) Convergence: The Unrealized Potential Of Pair Programming And Remote Work, Mikayla Maki

University Honors Theses

Remote work is expensive. It can lead to isolation, miscommunications, and ossified organizations. These problems occur because of a synchronicity mismatch between how we need to communicate as humans, and what today's tools are capable of. This mismatch can be solved by the adoption of remote pair programming, as exemplified by the authors work at a startup (Zed). Pair programming provides the organic, synchronous, reciprocal interaction necessary to develop the sorts of relationships that remote firms currently lack.

Attention Visual, Baris Dingil

College of Computing and Digital Media Dissertations

This research presents an innovative approach to improving visual-spatial attention using a research tool based on the web. Recognizing the significant role visual-spatial attention plays in everyday life and cognitive function for humans, this research was undertaken with the aim of developing a user-friendly, accessible web-based tool called Attention Visual (attentionvisual.com) to enhance this crucial cognitive skill. This tool also facilitates data collection, potentially accelerating the pace and enhancing the quality of related research. Both qualitative and quantitative methods were utilized for data collection and analysis. In order to stimulate improvements in visual-spatial attention, the tool’s algorithm was structured to …

Aisha: A Custom Ai Library Chatbot Using The Chatgpt Api, Yrjo Lappalainen, Nikesh Narayanan

All Works

This article focuses on the development of a custom chatbot for Zayed University Library (United Arab Emirates) using Python and the ChatGPT API. The chatbot, named Aisha, was designed to provide quick and efficient reference and support services to students and faculty outside the library's regular operating hours. The article also discusses the benefits of chatbots in academic libraries, and reviews the early literature on ChatGPT's applicability in this field. The article describes the development process, perceived capabilities and limitations of the bot, and plans for further development. This project represents the first fully reported attempt to explore the potential …

Planning For The Preservation Of Biodiversity And Environmental Assets In Support Of Sustainable Planning In Urban Areas, Case Study: Batu Licin City, Tanah Bumbu Regency, South Kalimantan, Dharma Kalsuma, Hendricus Andy Simarmata

Smart City

Planning for preserving biodiversity and environmental assets in urban areas is crucial in supporting sustainable planning. This study aims to design a strategy for preserving biodiversity and environmental assets in Batu Licin, Tanah Bumbu Regency, South Kalimantan, to support sustainable urban planning. The method used is field observation and literature study. The results showed that the Batu Licin area has a relatively high potential for biodiversity and environmental assets. However, along with the growth of the Batu Licin urban area in the future, it will undoubtedly be a source of pressure on biodiversity. Several strategies can be implemented to overcome …

A Novel Driver Emotion Recognition System Based On Deep Ensemble Classification, Khalid Zaman, Sun Zhaoyun, Babar Shah, Tariq Hussain, Sayyed Mudassar Shah, Farman Ali, Umer Sadiq Khan

All Works

Driver emotion classification is an important topic that can raise awareness of driving habits because many drivers are overconfident and unaware of their bad driving habits. Drivers will acquire insight into their poor driving behaviors and be better able to avoid future accidents if their behavior is automatically identified. In this paper, we use different models such as convolutional neural networks, recurrent neural networks, and multi-layer perceptron classification models to construct an ensemble convolutional neural network-based enhanced driver facial expression recognition model. First, the faces of the drivers are discovered using the faster region-based convolutional neural network (R-CNN) model, which …

A Multimodal Immune System Inspired Defense Architecture For Detecting And Deterring Digital Pathogens In Container Hosted Web Services, Islam Khalil

Theses and Dissertations

With the increased use of web technologies, microservices, and Application Programming Interface (API) for integration between systems, and with the development of containerization of services on operating system level as a method of isolating system execution and for easing the deployment and scaling of systems, there is a growing need as well as opportunities for providing platforms that improve the security of such services. In our work, we propose an architecture for a containerization platform that utilizes various concepts derived from the human immune system. The goal of the proposed containerization platform is to introduce the concept of slowing down …

Towards An Experimental Bibliography Of Hemispheric Reconstruction Newspapers, Joshua Ortiz Baco, Benjamin Charles Germain Lee, Jim Casey, Sarah H. Salter

Criticism

Digital collections of newspapers have drawn broader attention to the fragmented and scattered print histories of minoritized communities. Attempts to survey these histories through bibliography, however, quickly meet with a fundamental problem: the practice of bibliographic description calls for creating a static record of social affiliations. Given the overwhelming scholarly consensus that categories such as race, ethnicity, and language are socially constructed, this article introduces an experimental bibliographic method for mapping the vast landscape of historical newspapers. This method extends the machine learning affordances of a recent project called Newspaper Navigator to enumerate the newspapers in Chronicling America according to …

Quantifying Implicit Bias In Judicial Legal Opinions: A Natural Language Processing Approach, Philip N. Surendran

Quantitative Social Science Undergraduate Senior Theses

Implicit bias and criminal justice are two concepts that have long been intertwined. There is no justice without neutrality, and yet how do we tell if the actors enforcing the system are actually impartial? In this thesis, I utilize recent advancements in machine learning to attempt to answer this question. Specifically, I use natural language processing to examine the text of opinions written by judges in appellate courts, and I leverage these findings to build quantifiable measures of implicit bias. In particular, I look at the over/under-representation of certain emotions, sentiments and linguistic styles as a proxy for disparate treatment …

Sarcasm Detection In English And Arabic Tweets Using Transformer Models, Rishik Lad

Computer Science Senior Theses

This thesis describes our approach toward the detection of sarcasm and its various types in English and Arabic Tweets through methods in deep learning. There are five problems we attempted: (1) detection of sarcasm in English Tweets, (2) detection of sarcasm in Arabic Tweets, (3) determining the type of sarcastic speech subcategory for English Tweets, (4) determining which of two semantically equivalent English Tweets is sarcastic, and (5) determining which of two semantically equivalent Arabic Tweets is sarcastic. All tasks were framed as classification problems, and our contributions are threefold: (a) we developed an English binary classifier system with RoBERTa, …

Interstice, Shravan Rao

Masters Theses

When I was about three years old, I distinctly remember being too small to see what was on top of the table. A couple of years later, when I could see those objects, I thought the world around me had grown smaller. In a way, it did, as I experienced, lived, captured, remembered, and shared the space repeatedly. This sense of the world shrinking was exaggerated during the Covid-19 pandemic, allowing new behaviours and modes of interaction to emerge. Continually shaping our modern lives, virtual technologies redefine how we access and share information and stories or even explore new places. …

Counterfactual Replacement Analysis For Interpretation Of Blackbox Sexism Classification Models, Anders Knospe

Computer Science Senior Theses

This paper describes the AKD team’s system designed for SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS). We implement a simple fine-tuned GPT-3 model, ranking 26 on the leaderboard for task A. We also discuss different approaches to interpretability in the context of critiquing the EDOS task’s sub-category oriented approach. Finally, we propose counterfactual replacement analysis, a novel prototype technique for approaching explainability.

Ai Art: Artists’ Best Friend Or Mortal Enemy?, Ethan Gabrys

Tredway Library Prize for First-Year Research

This paper analyzes the impacts and implications of generative AI software on art and examines the ethics of using such tools. Through the argument that careless use of these tools presents a danger to the art world as they risk devaluing human expression, Gabrys states that “as what it means to be human changes with each generation, new artists express sentiment through their art. Art has the ability to tell us about the human experience.” He concludes that the use of AI tools takes the skill and sentiment of human artists out of the equation, begging the question: if the …