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Creating Talking Points For Client Advisers At Banks To Promote Sustainable Investing, Wewe Zi Yi, Pradeep Varakantham, Alan Megargel May 2025

Creating Talking Points For Client Advisers At Banks To Promote Sustainable Investing, Wewe Zi Yi, Pradeep Varakantham, Alan Megargel

Research Collection School Of Computing and Information Systems

Environmental, social and governance (ESG) factors have become key nonfinancial factors for investors to evaluate companies with respect to understanding material risks and growth opportunities. While not mandatory, companies are providing ESG reports that outline progress in different ESG metrics (six broad metrics and 15 specific ones). Client advisers (CAs) read these reports to identify key metrics of interest to investors. Given the number of companies and investment products, however, it is not feasible for CAs to read all the reports, which can sometimes run into tens or hundreds of pages). The authors have developed multiple frameworks building on leading …

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Tensorjsfuzz: Effective Testing Of Web-Based Deep Learning Frameworks Via Input-Constraint Extraction, Lili Quan, Xiaofei Xie, Qianyu Guo, Lingxiao Jiang, Sen Chen, Junjie Wang, Xiaohong Li May 2025

Tensorjsfuzz: Effective Testing Of Web-Based Deep Learning Frameworks Via Input-Constraint Extraction, Lili Quan, Xiaofei Xie, Qianyu Guo, Lingxiao Jiang, Sen Chen, Junjie Wang, Xiaohong Li

Research Collection School Of Computing and Information Systems

The 2025 ACM Web Conference (WWW '25) took place from April 28 to May 2, 2025, in the Sydney Convention & Exhibition Centre, Australia. Its logo, featuring the Sydney Harbour Bridge, symbolizes the core "connecting" function of the Web. Formerly known as the International World Wide Web Conference (WWW), this event originated at CERN in 1994 and has long served as the premier venue for presenting and discussing research, development, standards, and applications related to the Web.The 2025 ACM Web Conference (WWW'25) took place from April 28 to May 2, 2025, in the Sydney Convention & Exhibition Centre, Australia. Its …

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Sans: Efficient Densest Subgraph Discovery Over Relational Graphs Without Materialization, Yudong Niu, Yuchen Li, Jiaxin Jiang, Laks V. S. Lakshmanan May 2025

Sans: Efficient Densest Subgraph Discovery Over Relational Graphs Without Materialization, Yudong Niu, Yuchen Li, Jiaxin Jiang, Laks V. S. Lakshmanan

Research Collection School Of Computing and Information Systems

How can we efficiently identify the densest subgraph over relational graphs? Existing dense subgraph discovery (DSD) approaches assume that a relational graph H is already derived from a heterogeneous data source and they focus on efficient discovery of the densest subgraph on the materialized H. Unfortunately, materializing relational graphs can be resource-intensive, which thus limits the practical usefulness of existing algorithms over large datasets. To mitigate this, we propose a novel Summary-bAsed deNsest Subgraph discovery (SANS) system. Our unique summary-based peeling algorithm forms the core of SANS. Following the peeling paradigm, it utilizes summaries of each node's neighborhood to efficiently …

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Building Bridges Across Papua New Guinea’S Digital Divide In Growing The Ict Industry, Marc Cheong, Sankwi Abuzo, Hideaki Hata, Priscilla Kevin, Winifred Kula, Benson Mirou, Christoph Treude, Dong Wang, Raula Gaikovina Kula May 2025

Building Bridges Across Papua New Guinea’S Digital Divide In Growing The Ict Industry, Marc Cheong, Sankwi Abuzo, Hideaki Hata, Priscilla Kevin, Winifred Kula, Benson Mirou, Christoph Treude, Dong Wang, Raula Gaikovina Kula

Research Collection School Of Computing and Information Systems

Papua New Guinea (PNG) is an emerging tech society with an opportunity to overcome geographic and social boundaries, in order to engage with the global market. However, the current tech landscape, dominated by Big Tech in Silicon Valley and other multinational companies in the Global North, tends to overlook the requirements of emerging economies such as PNG. This is becoming more obvious as issues such as algorithmic bias (in tech product deployments) and the digital divide (as in the case of non-affordable commercial software) are affecting PNG users. The Open Source Software (OSS) movement, based on extant research, is seen …

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Enhancing Sub-Optimal Trajectory Stitching: Spatial Composition Rvs For Offline Rl, Sheng Zang, Zhiguang Cao, Bo An, Senthilnath Jayavelu, Xiaoli Li May 2025

Enhancing Sub-Optimal Trajectory Stitching: Spatial Composition Rvs For Offline Rl, Sheng Zang, Zhiguang Cao, Bo An, Senthilnath Jayavelu, Xiaoli Li

Research Collection School Of Computing and Information Systems

Reinforcement learning via supervised learning (RvS) has been known as a burgeoning paradigm for offline reinforcement learning (RL). While return-conditioned RvS (RvS-R) predominates across a wide range of datasets pertaining to the offline RL tasks, recent findings suggest that goal-conditioned RvS (RvS-G) outperforms in specific sub-optimal datasets where trajectory stitching is crucial for achieving optimal performance. However, the underlying reasons for this superiority remain insufficiently explored. In this paper, employing didactic experiments and theoretical analysis, we reveal that the proficiency of RvS-G in stitching trajectories arises from its adeptness in generalizing to unknown goals during evaluation. Building on this insight, …

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“Ronaldo’S A Poser!”: How The Use Of Generative Ai Shapes Debates In Online Forums, Yuhan Zeng, Yingxuan Shi, Xuehan Huang, Fiona Fui-Hoon Nah, Ray Lc May 2025

“Ronaldo’S A Poser!”: How The Use Of Generative Ai Shapes Debates In Online Forums, Yuhan Zeng, Yingxuan Shi, Xuehan Huang, Fiona Fui-Hoon Nah, Ray Lc

Research Collection School Of Computing and Information Systems

Online debates can enhance critical thinking but may escalate into hostile attacks. As humans are increasingly reliant on Generative AI (GenAI) in writing tasks, we need to understand how people utilize GenAI in online debates. To examine the patterns of writing behavior while making arguments with GenAI, we created an online forum for soccer fans to engage in turn-based and free debates in a post format with the assistance of ChatGPT, arguing on the topic of "Messi vs Ronaldo". After 13 sessions of two-part study and semi-structured interviews with 39 participants, we conducted content and thematic analyses to integrate insights …

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Iot In Sustainability And Iot In The Ai And Metaverse Age, Yuzhou Qian, Keng Siau May 2025

Iot In Sustainability And Iot In The Ai And Metaverse Age, Yuzhou Qian, Keng Siau

Research Collection School Of Computing and Information Systems

The Internet of Things (IoT) is a modern technology that has gained large popularity and is still developing. Connecting heterogeneous devices, such as phones, vehicles, and household appliances, IoT has brought convenience to our lives. Further, IoT plays a significant role in enhancing environmental sustainability. It provides timely data about different devices and enables users and managers to directly control the objects. IoT can optimize the existing energy systems and promote the usage of renewable technologies. In this paper, we discuss how IoT supports green initiatives (i.e., how it is applied in different sectors), how it can be "green" itself …

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Flexfl: Flexible And Effective Fault Localization With Open-Source Large Language Models, Chuyang Xu, Zhongxin Liu, Xiaoxue Ren, Gehao Zhang, Ming Liang, David Lo May 2025

Flexfl: Flexible And Effective Fault Localization With Open-Source Large Language Models, Chuyang Xu, Zhongxin Liu, Xiaoxue Ren, Gehao Zhang, Ming Liang, David Lo

Research Collection School Of Computing and Information Systems

Fault localization (FL) targets identifying bug locations within a software system, which can enhance debugging efficiency and improve software quality. Due to the impressive code comprehension ability of Large Language Models (LLMs), a few studies have proposed to leverage LLMs to locate bugs, i.e., LLM-based FL, and demonstrated promising performance. However, first, these methods are limited in flexibility. They rely on bug-triggering test cases to perform FL and cannot make use of other available bug-related information, e.g., bug reports. Second, they are built upon proprietary LLMs, which are, although powerful, confronted with risks in data privacy. To address these limitations, …

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Sigscope: Detecting And Understanding Off‑Chain Message Signing‑Related Vulnerabilities In Decentralized Applications, Sajad Meisami, Hugo Dabadie, Song Li, Yuzhe Tang, Yue Duan May 2025

Sigscope: Detecting And Understanding Off‑Chain Message Signing‑Related Vulnerabilities In Decentralized Applications, Sajad Meisami, Hugo Dabadie, Song Li, Yuzhe Tang, Yue Duan

Research Collection School Of Computing and Information Systems

In Web 3.0, an emerging paradigm of building decentralized applications or DApps is off-chain message signing, which has advantages in performance, cost efficiency, and usability compared to conventional transaction-signing schemes. However, message signing burdens DApp developers with extra coding complexity and message designing, leading to new security risks.This paper presents the first systematic study to uncover and characterize the security issues in off-chain message signing schemes and the DApps built atop them. We present a holistic static-analysis framework, SigScope, that uniquely combines the insights extracted from DApp front-end code (HTML and Javascript) off-chain and back-end smart contracts on-chain. We evaluate …

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Real-Time Rectifying Flight Control Misconfiguration Using Intelligent Agent, Ruidong Han, Shangzhi Xu, Juanru Li, Elisa Bertino, David Lo, Jianfeng Ma, Siqi Ma May 2025

Real-Time Rectifying Flight Control Misconfiguration Using Intelligent Agent, Ruidong Han, Shangzhi Xu, Juanru Li, Elisa Bertino, David Lo, Jianfeng Ma, Siqi Ma

Research Collection School Of Computing and Information Systems

Configurations are supported by most flight control systems, allowing users to control a flying drone adapted to complexities such as environmental changes or mission alterations. Such an advanced functionality also introduces a significant problem—misconfiguration settings. It may cause drone instability, threaten drone safety, and potentially lead to substantial financial loss. However, detecting and rectifying misconfigurations across different flight control systems is challenging because (1) (mis)configuration-related code snippets might be syntactically correct and thus hard to identify through traditional code analysis; (2) the response to each configuration varies under different flying scenarios.In this article, we propose and implement a novel rectification …

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Toward Better Comprehension Of Breaking Changes In The Npm Ecosystem, Dezhen Kong, Jiakun Liu, Lingfeng Bao, David Lo May 2025

Toward Better Comprehension Of Breaking Changes In The Npm Ecosystem, Dezhen Kong, Jiakun Liu, Lingfeng Bao, David Lo

Research Collection School Of Computing and Information Systems

Code evolution is prevalent in software ecosystems, which can provide many benefits, such as new features, bug fixes, security patches, while still introducing breaking changes that make downstream projects fail to work. Breaking changes cause a lot of effort to both downstream and upstream developers: downstream developers need to adapt to breaking changes and upstream developers are responsible for identifying and documenting them. In the NPM ecosystem, characterized by frequent code changes and a high tolerance for making breaking changes, the effort is larger.For better comprehension of breaking changes in the NPM ecosystem and to enhance breaking change detection tools, …

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Seaexam And Seabench: Benchmarking Llms With Local Multilingual Questions In Southeast Asia, Chaoqun Liu, Wenxuan Zhang, Jiahao Ying, Mahani Aljunied, Anh Tuan Luu, Lidong Bing May 2025

Seaexam And Seabench: Benchmarking Llms With Local Multilingual Questions In Southeast Asia, Chaoqun Liu, Wenxuan Zhang, Jiahao Ying, Mahani Aljunied, Anh Tuan Luu, Lidong Bing

Research Collection School Of Computing and Information Systems

This study introduces two novel benchmarks, SeaExam and SeaBench, designed to evalu ate the capabilities of Large Language Models (LLMs) in Southeast Asian (SEA) application scenarios. Unlike existing multilingual datasets primarily derived from English translations, these benchmarks are constructed based on real world scenarios from SEA regions. SeaExam draws from regional educational exams to form a comprehensive dataset that encompasses sub jects such as local history and literature. In contrast, SeaBench is crafted around multi turn, open-ended tasks that reflect daily inter actions within SEA communities. Our evalua tions demonstrate that SeaExam and SeaBench more effectively discern LLM performance on …

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From The Bleachers To The Browser: Redefining Fan Experience With Ar And Ai In Smaller Teams, Jennifer Lee Wunder May 2025

From The Bleachers To The Browser: Redefining Fan Experience With Ar And Ai In Smaller Teams, Jennifer Lee Wunder

Theses

This project documents the creation and deployment of HootyHoo, an interactive augmented reality (AR) mascot experience designed for the O’Fallon Hoots, a small-scale collegiate summer baseball team. Built using accessible, open-source tools such as WebXR, Mixamo, Meshy, Botpress, Claude and ChatGPT, this prototype merges AI-driven conversation with animated 3D avatar interaction—redefining how fans engage with sports organizations digitally. Unlike enterprise-level applications used by professional franchises, HootyHoo is entirely browser-based, eliminating the need for app downloads and ensuring maximum accessibility for families and new fans with smartphones. The experience centers on Hooty, the team mascot, who answers questions about baseball and …

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Eduqate: Generating Adaptive Curricula Through Rmabs In Education Settings, Sidney Tio, Dexun Li, Pradeep Varakantham May 2025

Eduqate: Generating Adaptive Curricula Through Rmabs In Education Settings, Sidney Tio, Dexun Li, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

There has been significant interest in the development of personalized and adaptive educational tools that cater to a student's individual learning progress. A crucial aspect in developing such tools is in exploring how mastery can be achieved across a diverse yet related range of content in an efficient manner. While Reinforcement Learning and Multi-armed Bandits have shown promise in educational settings, existing works often assume the independence of learning content, neglecting the prevalent interdependencies between such content. In response, we introduce Education Network Restless Multi-armed Bandits (EdNetRMABs), utilizing a network to represent the relationships between interdependent arms. Subsequently, we propose …

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Achieving Fairness In Zoning Laws With Machine Learning, William Schimitsch May 2025

Achieving Fairness In Zoning Laws With Machine Learning, William Schimitsch

College Honors Program

Zoning is a powerful regulatory tool that determines how municipalities use and develop land. The goal of zoning is to classify land use (e.g., residential, commercial, industrial) to maximize compatibility among neighboring parcels. Local zoning decisions, however, are made by small-sized boards, often through an opaque process, which raises concerns about bias and fairness. In the United States, zoning has historically prioritized single-family housing and thus created economic barriers that limit access to certain communities. Given the task of classifying land use and the wealth of geographical, demographic, and infrastructural data describing each parcel, the problem of bias in zoning …

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Divergence-Free Smoothed Particle Hydrodynamics In A Stream Digital Twin, Austin Hartley May 2025

Divergence-Free Smoothed Particle Hydrodynamics In A Stream Digital Twin, Austin Hartley

All Theses

Digital Twins (DT) are being explored by the South Carolina (SC) water community to simulate how SC streams will flow at various water levels. Currently, a DT called Gilligan simulates these streams utilizing weakly-incompressible Smoothed Particle Hydrodynamics (SPH). This method does not strictly enforce incompressibility, which leads to unrealistic water flows and unwanted visual artifacts that require post-processing effects to hide. To address these problems and simulate more realistic water flows, the Gilligan stream logic is updated and a state-of-the-art SPH method that enforces incompressibility—Divergence-Free SPH (DFSPH)—is implemented within the Gilligan framework. DFSPH is able to make use of two …

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Understanding The Impact Of Ransomware On Biotechnology, Tswvyim Vang May 2025

Understanding The Impact Of Ransomware On Biotechnology, Tswvyim Vang

Electronic Theses, Projects, and Dissertations

Biotechnology encompasses the use of research on both biology and technology to create products that can advance in areas such as healthcare and agriculture. Because of the technology and products that arise from the use of biotechnology, the industry is especially targeted by cyber-attacks. A prominent type of cyber-attack that is utilized by cyber criminals on biotechnology is ransomware. The goal of this project is to determine the impact of ransomware on biotechnology. The research questions posed are: Q1) What are real examples of ransomware attacks that have occurred on biotechnology companies and what patterns can be identified by these …

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Early Breast Cancer Detection With Ultrasound Data Using Nmf, Rutvi Khamar May 2025

Early Breast Cancer Detection With Ultrasound Data Using Nmf, Rutvi Khamar

Theses and Dissertations

Early detection of breast cancer significantly influences patient outcomes. Dynamic Contrast-Enhanced Ultrasound (DCE-US) has shown promise in early detection by visualizing tumor vascularity and perfusion dynamics in real-time. This study evaluates the efficacy of DCE-US in distinguishing four stages of cancer progression: normal, hyperplasia, ductal carcinoma in situ (DCIS), and invasive cancer, using a transgenic mouse model that mimics human breast cancer. Ultrasound burst pulses, while commonly used to remove unbound contrast agents, can potentially damage human tissues. Using the pre-pulse data helps mitigate this risk, ensuring safer and more reliable measurements. A VEGFR2-targeted microbubble contrast agent was injected, and …

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Quasipseudometric Value Functions With Dense Rewards, Khadichabonu Valieva May 2025

Quasipseudometric Value Functions With Dense Rewards, Khadichabonu Valieva

Honors Theses

Goal-conditioned reinforcement learning (GCRL) serves as an extension of reinforce- ment learning (RL) that focuses on goals that can be adjusted, making it useful for many applications, especially in complex robotics tasks. Recent research has established that the optimal value function of GCRL, denoted as Q∗(s, a, g), has a quasipseudometric structure. This finding has led to the development of targeted neural architectures that respect such a structure. However, prior analyses have predominantly focused on sparse reward settings, which are known to increase challenges related to sample complexity. In this work, I with the guidance of my advisor show that …

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Privacy-Aware Ai-Based Agricultural Monitoring Using Internet Of Drones, Md Benozir Hossain May 2025

Privacy-Aware Ai-Based Agricultural Monitoring Using Internet Of Drones, Md Benozir Hossain

Honors Theses

Artificial Intelligence (AI) has become a vital tool for agricultural farming. AI-based image processing models utilizing different machine learning (ML) algorithms and deep learning (DL) offer advanced functionalities in disease detection, yield estimation, land use, etc. This thesis examines AI-driven techniques utilizing Convolutional Neural Networks (CNN) with the addition of Federated Learning (FL) to analyze satellite and drone images for agricultural insights, especially in detecting Cotton diseases. The AI models improve agricultural farming in many ways, such as using data to make critical decisions, reducing labor costs, pest infestations, etc. Moreover, these models allow farmers to minimize yield losses by …

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Building Toward A Text-Based Intervention For Parents Of Suicidal Adolescents Seeking Emergency Department Care: A Pilot Randomized Controlled Trial., Ewa Czyz, Inbal Nahum-Shani, Cynthia Ewell Foster, Valerie Micol, Amanda Jiang, Nadia Al-Dajani, Alejandra Arango, Maureen Walton, Victor Hong, Sheikh Iqbal Ahamed, Cheryl King May 2025

Building Toward A Text-Based Intervention For Parents Of Suicidal Adolescents Seeking Emergency Department Care: A Pilot Randomized Controlled Trial., Ewa Czyz, Inbal Nahum-Shani, Cynthia Ewell Foster, Valerie Micol, Amanda Jiang, Nadia Al-Dajani, Alejandra Arango, Maureen Walton, Victor Hong, Sheikh Iqbal Ahamed, Cheryl King

Computer Science Faculty Research and Publications

Objective: The growing demand for emergency department (ED) care for suicidal ideation and attempts in adolescents calls for effective interventions preventing post-ED recurrence of suicidal crises. Parents are tasked with implementing postdischarge suicide prevention recommendations, often with little support. To address this need, this study examined a parent-facing texting intervention targeting parental engagement in suicide prevention activities to lower youth suicide risk after discharge. Method: A pilot randomized controlled trial was conducted with 120 parents (83.3% mothers) and their adolescents (ages 13–17, 65.8% female, 75.0% White) presenting to an ED with suicide risk concerns. Parents were randomized to a control …

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Predicting Healthcare Service Quality Based On A Kalman-Optimized Bi-Lstm-Inspired Deep Learning Model, Mohammed K. Al-Khafaji, Eman S. Al-Shamery Apr 2025

Predicting Healthcare Service Quality Based On A Kalman-Optimized Bi-Lstm-Inspired Deep Learning Model, Mohammed K. Al-Khafaji, Eman S. Al-Shamery

Karbala International Journal of Modern Science

Health is one of the most important aspects of human well-being, and access to high-quality healthcare is essential for a good quality of life. Providing top-level health services at all times is crucial. However, the research in healthcare poses significant challenges due to the diversity and variations of medical practices across different hospitals. This paper aims to tackle the challenge of data missing and scattering during data collection. Then, the quality of services (QoS) offered by healthcare facilities will be analyzed and predicted from the patient's perspective. The model begins preprocessing data by data cleaning, handling missing values, and scattering …

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The Role Of Individual Values In Bryant University's Sustainability Efforts, John Boccuzzi Iii Apr 2025

The Role Of Individual Values In Bryant University's Sustainability Efforts, John Boccuzzi Iii

Honors Projects in Data Science

This research examines student, faculty, and staff perspectives on sustainability at Bryant University, with the goal of understanding how individual values align with the university's environmental initiatives. The objective is to assess perceptions of Bryant's current sustainability practices, explore how effectively these efforts are communicated across campus, and identify potential gaps between institutional action and community awareness. To achieve this, the study gathers qualitative data through an open-ended survey and applies sentiment analysis to interpret student attitudes toward sustainability. By analyzing these responses alongside Bryant's sustainability marketing efforts, this research will identify gaps between student engagement and institutional messaging The …

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Artificial Intelligence In Orthopedic Medical Education: A Comprehensive Review Of Emerging Technologies And Their Applications, Kyle Sporn, Rahul Kumar, Phani Paladugu, Tejas Sekhar, Swapna Vaja, Tamer Hage, Ethan Waisberg, Chirag Gowda, Ram Jagadeesan, Nasif Zaman, Alireza Tavakkoli Apr 2025

Artificial Intelligence In Orthopedic Medical Education: A Comprehensive Review Of Emerging Technologies And Their Applications, Kyle Sporn, Rahul Kumar, Phani Paladugu, Tejas Sekhar, Swapna Vaja, Tamer Hage, Ethan Waisberg, Chirag Gowda, Ram Jagadeesan, Nasif Zaman, Alireza Tavakkoli

SKMC Student Presentations and Publications

Integrating artificial intelligence (AI) and mixed reality (MR) into orthopedic education has transformed learning. This review examines AI-powered platforms like Microsoft HoloLens, Apple Vision Pro, and HTC Vive Pro, which enhance anatomical visualization, surgical simulation, and clinical decision-making. These technologies improve the spatial understanding of musculoskeletal structures, refine procedural skills with haptic feedback, and personalize learning through AI-driven adaptive algorithms. Generative AI tools like ChatGPT further support knowledge retention and provide evidence-based insights on orthopedic topics. AI-enabled platforms and generative AI tools help address challenges in standardizing orthopedic education. However, we still face many barriers that relate to standardizing data, …

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A Critical Realist Erp Implementation In Zimbabwean Mining Industry Organisations, Jairos Mukwenha Apr 2025

A Critical Realist Erp Implementation In Zimbabwean Mining Industry Organisations, Jairos Mukwenha

Tanzania Journal of Engineering and Technology (TJET)

This research uses a critical realist framework to examine the factors influencing the success of enterprise resource planning (ERP) system implementation in Zimbabwean mining industry organisations. From the perspective of critical realism, the mining industry in Zimbabwe faces a complex interplay of opportunities and obstacles while implementing ERP systems. The deployment of ERP in mining firms is critically examined in this paper, emphasising how these systems might improve operational efficiency while considering Zimbabwe's particular socioeconomic circumstances. By exploring underlying structures, mechanisms, and outcomes, the research aims to identify critical challenges and opportunities and develop practical recommendations for improving ERP adoption …

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Development Of A Microcontroller-Based Intelligent Traffic Light Control System For Vehicular Movement In T-Junctions, Frederick O. Ehiagwina Apr 2025

Development Of A Microcontroller-Based Intelligent Traffic Light Control System For Vehicular Movement In T-Junctions, Frederick O. Ehiagwina

Tanzania Journal of Engineering and Technology (TJET)

This research is devoted to the issue of regulating traffic congestion in major cities using light-dependent resistors coupled with the PIC16F877A microcontroller. This study proposes an intelligent traffic control system for T-Junctions, utilizing sensing and control to optimize traffic flow through dynamic phase adjustments and congestion reduction, enabled by a microcontroller-based decision-making system. The proposed system reduces traffic congestion, automates control, and enhances safety, minimizing accidents and lowering infrastructure costs. Under simulated environment, it demonstrates an average response time of 50 ms and achieves 99% accuracy in displaying the correct countdown. Finally, the number of state transitions handled per minute …

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Infusing Aboriginal Perspectives In Cyber Education, John Shannahan, Mohiuddin Ahmed Apr 2025

Infusing Aboriginal Perspectives In Cyber Education, John Shannahan, Mohiuddin Ahmed

Research outputs 2022 to 2026

While human factors are important in cyber security, the discipline has largely not explored incorporating indigenous perspectives—or, more specifically, in an Australian context, Aboriginal perspectives—in its curricula. In this paper, we introduce a promising approach for aligning Aboriginal perspectives with the needs of cyber security graduates and incorporating diverse perspectives into cyber degrees. The approach advocates for the centrality of good curriculum design fundamentals: backward design, constructive alignment, and student outcomes. The paper ends by reflecting on challenges and lessons from the first implementation and review of the material. It provides recommendations for other cyber practitioners exploring ways of incorporating …

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An Efficient Blockchain-Based Privacy Preservation Scheme For Smart Grids, Mohamad Badra, Rouba Borghol Apr 2025

An Efficient Blockchain-Based Privacy Preservation Scheme For Smart Grids, Mohamad Badra, Rouba Borghol

All Works

Smart grids have revolutionized electricity management and distribution, but they also generate and transmit vast amounts of consumer data, raising privacy concerns. In this paper, we propose a blockchain-based solution to preserve user's privacy in smart grids and to mitigates data forgery, profiling, and man-in-the-middle attacks. Moreover, our solution provides security services such as authentication and non-repudiation to prevent unauthorized access to sensitive data and ensure accountability and traceability. We validate our approach through testing and show that it is a simple, scalable, cost-effective solution with minimal computational processing overhead.

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Generating More Equitable Fair Use, Jacqueline Kessel Apr 2025

Generating More Equitable Fair Use, Jacqueline Kessel

Pepperdine Law Review

From advancing healthcare and education to threatening democratic systems, generative artificial intelligence (AI) has demonstrated a capacity to positively and negatively impact society. And these benefits and consequences are not shared equitably. Copyright law, however, stands as a powerful mechanism in monitoring AI system development. Several complaints have charged generative AI system developers with copyright infringement, alleging that (1) ingesting copyrighted works as training data infringes the copyright owner’s exclusive right to reproduce works in copies and (2) generating AI outputs infringes the exclusive right to prepare derivative works because the outputs are based upon the works on which the …

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Self-Supervised Learning And Its Applications In Medical Image Analysis, Siladittya Manna Apr 2025

Self-Supervised Learning And Its Applications In Medical Image Analysis, Siladittya Manna

Doctoral Theses

Self-supervised learning (SSL) enables learning robust representations from unlabeled data and it consists of two stages: pretext and downstream. The representations learnt in the pretext task are transferred to the downstream task. Self-supervised learning has appli- cations in various domains, such as computer vision tasks, natural language processing, speech and audio processing, etc. In transfer learning scenarios, due to differences in the data distribution of the source and the target data, the hierarchical co-adaptation of the representations is destroyed, and hence proper fine-tuning is required to achieve satisfactory performance. With self-supervised pre-training, it is possible to learn repre- sentations aligned …

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