Digital Commons Network^™

Problem-Centered Post-Secondary Computer Science Education: A Study Of The Private Artificial Intelligence Curriculum, Golnoush Haddadian, Prajwal Panzade, Daniel Takabi, Min Kyu Kim

School of Cybersecurity Faculty Publications

In response to the demand for Artificial Intelligence (AI) experts, this study introduced a curriculum development initiative. The aim was to design and implement a Private AI curriculum to understand the computer science (CS) students’ evaluations of the curricular activities and their levels of interest and motivation. Twenty-five students, a mix of undergraduates and graduates, were recruited and a scaled-down version of the curriculum was implemented. A parallel mixed-methods approach was employed. The results reinforced the significance of problem-centered curricula in CS context. Students rated the curricular activities highly and demonstrated strong motivation; however, graduates expressed more favorable view of …

Privacy-Preserved And Incentivized Knowledge Sharing For Reinforced-Learning Based Iot Platform Security, Weichao Wang, Md Morshed Alam, Yu Wang

School of Cybersecurity Faculty Publications

With the fast development and deep penetration of IoT devices and smart environments, using localized machine learning models to detect malicious activities has also been developed and deployed. However, these isolated learning models and results cannot be effectively federated together because of privacy concerns and lack of incentivization. This paper proposed several mechanisms to solve the problem. A verification method was designed for phased learning results to protect user privacy and prevent individual parties from manipulating the verification selection. The paper also presented an incentive method based on delay of distribution of the latest federated learning results. Extensive simulations were …

Security Enhancement In Uav Swarms: A Case Study Using Federated Learning And Shap Analysis, Sushmitha Halli Sudhakara, Lida Haghnegahdar

School of Cybersecurity Faculty Publications

As cyber-physical systems (CPSs) increasingly integrate physical and digital realms, securing critical infrastructure, such as the Port of Virginia, becomes paramount. Among CPSs, Unmanned Aerial Vehicles (UAVs) are vital for monitoring, communication, and supporting the command and control through remote reconnaissance and surveillance missions. These UAV applications often require coordination, planning, and runtime reconfiguration, traditionally managed by human decision-makers. However, this approach has limitations, as extensively documented in the literature. Artificial Intelligence (AI) has emerged as a pivotal tool to address these limitations, enhancing risk mitigation and informed decision-making. This research proposes a machine learning (ML) based security mechanism, leveraging …

Security Enhancement In Aav Swarms: A Case Study Using Federated Learning And Shap Analysis, Sushmitha Halli Sudhakara, Lida Haghnegahdar

School of Cybersecurity Faculty Publications

As cyber-physical systems (CPSs) increasingly integrate physical and digital realms, securing critical infrastructure, such as the Port of Virginia, becomes paramount. Among CPSs, Autonomous Aerial Vehicles (AAVs) are vital for monitoring, communication, and supporting the command and control through remote reconnaissance and surveillance missions. These AAV applications often require coordination, planning, and runtime reconfiguration, traditionally managed by human decision-makers. However, this approach has limitations, as extensively documented in the literature. Artificial Intelligence (AI) has emerged as a pivotal tool to address these limitations, enhancing risk mitigation and informed decision-making. This research proposes a machine learning (ML) based security mechanism, leveraging …

Long-Term Traffic Prediction Using Deep Learning Long Short-Term Memory, Ange-Lionel Toba, Sameer Kulkarni, Wael Khallouli, Timothy Pennington

School of Cybersecurity Faculty Publications

Traffic conditions are a key factor in our society, contributing to quality of life and the economy, as well as access to professional, educational, and health resources. This emphasizes the need for a reliable road network to facilitate traffic fluidity across the nation and improve mobility. Reaching these characteristics demands good traffic volume prediction methods, not only in the short term but also in the long term, which helps design transportation strategies and road planning. However, most of the research has focused on short-term prediction, applied mostly to short-trip distances, while effective long-term forecasting, which has become a challenging issue …

Tl-Convlstm: A Transfer-Learning-Based Convolutional Lstm To Identify And Forecast Traffic In The Nextg Environments, Bikash Chandra Singh, Peter Foytik, Rafael Diaz, Sachin Shetty

School of Cybersecurity Faculty Publications

Forecasting and categorizing cellular traffic flows and their types are essential functions in intelligent network systems to ensure efficient network optimization. The ever-evolving nature of 5G networks results in fluctuations in traffic patterns over time, leading to a phenomenon known as model drift. Consequently, accurately predicting and identifying cellular traffic patterns becomes a complex task. To tackle this challenge, this article introduces an innovative approach called TL-ConvLSTM, which combines transfer learning with convolutional long short-term memory (ConvLSTM) to effectively combat model drift and provide precise forecasting and recognition of cellular traffic within the network. To accomplish this, we initiate the …

Qos-Aware Link Adaptation For Beyond 5g Networks: A Deep Reinforcement Learning Approach, Ali Parsa, Neda Moghim, Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

Modern wireless communication systems face increasingly complex challenges due to rapidly changing channel conditions and the growing diversity of application-specific Quality of Service (QoS) requirements. Traditional link adaptation mechanisms primarily aim to maximize throughput and often lack the flexibility to support emerging applications, such as Extended Reality (XR) and Virtual Reality (VR), which demand simultaneous guarantees for high data rates, ultra low latency, and high reliability. These stringent and multidimensional QoS needs call for more intelligent and adaptive solutions. In this paper, we propose QDRLLA (QoS-aware Deep Reinforcement Learning-based Link Adaptation), a novel framework that employs deep reinforcement learning to …

A Trust-By-Learning Framework For Secure 6g Wireless Networks Under Native Generative Ai Attacks, Md Shirajum Munir, Sravanthi Proddatoori, Manjushree Muralidhara, Trinidad Mario Dena, Walid Saad, Zhu Han, Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

Sixth-generation (6G) wireless networks will become vulnerable due to native generative AI (GenAI)-driven intelligent poisoning attacks in both the radio unit and the core network. In particular, network parameters and metrics in cross-layer design pose fundamentally uncertain conditions and can be compromised through the native GenAI mechanism, which leverages data augmentation and reconstruction capabilities. This work investigates the capabilities of native GenAI to create novel poisoning attacks in wireless networks, while investigating their impact through uncertainty-informed root analysis. Then, detected attacks are mitigated by developing a trustworthy service aggregation in the wireless network. First, a joint decision problem is formulated …

Empowering Customer Service With Generative Ai: Enhancing Agent Performance While Navigating Challenges, Charles Costa, Souvick Ghosh

Faculty Research, Scholarly, and Creative Activity

Introduction. As large language models (LLMs), such as GPTs, become more intelligent, a key area of exploration is how these technologies can improve the customer experience. Contrary to common belief, many consumers, including Gen Z, prefer human-provided customer service, illustrating the importance of human-AI collaboration in the space. Method. By leveraging the author’s real-world knowledge of enterprise knowledge management and customer service delivery, we reviewed numerous literature about AI, knowledge management, and service design and synthesised practical insights for industry professionals to build a successful AI strategy. Analysis. We examined the gap between academic research on generative AI and how …

Using A Sober Curious Framework To Explore Barriers And Facilitators To Helping Sexual Minority Women Reduce Alcohol-Related Harms: Protocol For A Descriptive Study, Tonda L. Hughes, Lauren Bochicchio, Laurie A. Drabble, Belinda Lunnay, David Whiteley, Jillian R. Scheer, Beth Meadows, Paul Ward, Carol Emslie

Faculty Research, Scholarly, and Creative Activity

Background: Globally, women consume less alcohol than men, but alcohol consumption among women has declined less in recent years than among men. Drinking rates and alcohol-related harms vary substantially across population groups of women, and sexual minority women (eg, lesbian, bisexual, and queer) are at notably high risk. An emerging body of literature suggests that in addition to minority stress (eg, stigma, discrimination), drinking norms and drinking cultures likely influence sexual minority women’s drinking. Almost no research has explored these factors as possible targets of interventions. Sober curiosity is a rapidly growing wellness movement that may be particularly salient for …

Morphometric Characterization Of Invasive Diaphorina Citri Infesting Citrus And Orange Jasmine In Ghana, Kodwo Dadzie Ninsin, Maxwell Kelvin Billah, Bernard Agyeman Boateng, Jonathan Osei-Owusu, Fred Kormla Ablormeti, Samuel Opuni-Basoa, Aboagye Kwarteng Dofuor, George Edusei, Steve B.S. Baleba, Owusu Fordjour Aidoo

All Peer-Reviewed Publications

Morphometric analysis plays a crucial role in the accurate identification and classification of insect pests, which is essential for implementing effective management strategies. The Asian citrus psyllid (Diaphorina citri Kuwayama; Hemiptera: Liviidae), an invasive species and a known vector of ‘Candidatus Liberibacter asiaticus’ and ‘Ca. Liberibacter americanus,’ the bacterial pathogens associated with Huanglongbing (HLB), has recently emerged as a pest of concern in Ghana. Despite its significance, little is known about the biological traits of field populations in the region. In this study, we examined morphometric variation in D. citri populations infesting citrus and orange jasmine (Murraya paniculata) across different …

A Review On Knowledge And Information Extraction From Pdf Documents And Storage Approaches, Salvador D. Atagong, Henri Tonnang, Kennedy Senagi, Mark Wamalwa, Komi M. Agboka, John Odindi

All Peer-Reviewed Publications

Introduction: Automating the extraction of information from Portable Document Format (PDF) documents represents a major advancement in information extraction, with applications in various domains such as healthcare, law, or biochemistry. However, existing solutions face challenges related to accuracy, domain adaptability, and implementation complexity. Methods: A systematic review of the literature was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to examine approaches and trends in PDF information extraction and storage approaches. Results: The review revealed three dominant methodological categories: rule-based systems, statistical learning models, and neural network-based approaches. Key limitations include the rigidity of rule-based …

Insect Biological Control: A Global Perspective, Lessando M. Gontijo, Jorge B. Torres, Paul K. Abram, Armando Alfaro-Tapia, Hugo C. Arredondo-Bernal, Antonio Biondi, Raymond A. Cloyd, Alejandro C. Costamagna, Nicolas Desneux, Marie D’Ottavio, Michael J. Furlong, Nancy M. Greco, Roselyne Labbe, Martin Hill, Blas Lavandero, Tian Hao Li, José R. Lomelí-Flores, Eric Lucas, Gerben J. Messelink, Margarita Rocca, Marcela Rodriguez-Garcia, José R.P. Parra, Ainara Peñalver-Cruz, Bonoukpoè Mawuko Sokame, Sean Thackeray, Alberto Urbaneja, German Vargas, Myron P. Zalucki, Lian Sheng Zang

All Peer-Reviewed Publications

The intentional use of biological control agents to manage arthropod pests dates back to as early as 304 AD, when Chinese farmers used weaver ants to manage citrus pests. Over time, biological control has evolved into distinct approaches: classical, augmentation, and conservation. Prior to the advent of pesticides, most insect pest management relied on natural and classical biological control. The most common strategy used at first, despite regional variations, was the importation of biological control agents. Nonetheless, due to issues with unintentional non-target impacts, numerous failures in the introduction, and longer periods required for implementation, augmentative and conservation approaches have …

The Effectiveness Of Tech Support Fraud In Damaging Older Individual’S Financial Security, Vanessa Perera

Theses : Honours

This study discovers the tactics employed to create detrimental effects upon older people impacted from fraudulent tech-support incidents. It examines social engineering, and financial confusion of older people. This is significant considering adaptations towards digital banking and payment management. This research looked at online and active over 65s. Using largely qualitative approaches over 65s were interviewed and responses validated against cyber-professionals’ responses. This identified three key findings: older adults feel confused and misunderstand tech support scams; threat actors build trust by pretending to offer technical help but use this to deceive their victims; and older adults face serious social and …

Cochlear Implantation With Sporadic Inner Ear Schwannomas: Outcomes In 106 Patients From An International Multi-Institutional Study, John P. Marinelli, Torsten Rahne, James R. Dornhoffer, Christine M. Lohse, Justin Cottrell, J. Thomas Roland, Nicholas J. Thompson, Kevin D. Brown, Jacob C. Lucas, Seilesh C. Babu, Nathan R. Lindquist, Elizabeth L. Perkins, Donald Tan, John I. Lane, Jacob B. Hunter, Erin Harvey, Nicholas L. Deep, Samantha Y. Cerasiello, Matthew L. Kircher, Mana Espahbodi, Evan L. Tooker, Niels Cramer West, Per Caye-Thomasen, Matthew L. Carlson, Stefan K. Plontke

Department of Otolaryngology - Head and Neck Surgery Faculty Papers

OBJECTIVE: To evaluate cochlear implant speech perception among patients with sporadic inner ear schwannoma who underwent ipsilateral implantation.

STUDY DESIGN: Retrospective multi-institutional cohort study.

SETTING: Eleven tertiary academic medical centers across Germany, Denmark, and the United States.

PATIENTS: One hundred six patients with sporadic inner ear schwannoma who received an ipsilateral cochlear implant from 2011 to 2022.

INTERVENTIONS: Ipsilateral cochlear implantation with observation, stereotactic radiosurgery, or microsurgery for tumor management.

MAIN OUTCOME MEASURES: Monosyllabic speech perception testing scores and rates of open-set speech perception.

RESULTS: Among 106 patients studied, 101 (95%) achieved open-set speech perception with a median of 24 …

Exodus. Teacher's Edition: Adult Sabbath School Bible Study Guide, Jiri Moskala

All Books

No abstract provided.

Challenging Behaviour In The Early Years: Investigating Teacher Perceptions, Gillian Anne Smith

Theses: Doctorates and Masters

An upward national trend in challenging behaviour amongst young children in Australian schools has prompted widespread concern and garnered frequent media scrutiny. Scholars have established that child-teacher relationships are central to understanding and mitigating challenging behaviour; however, exploration of teacher perceptions of children’s challenging behaviour in the early years has been limited. This study aimed to address this gap by investigating how early childhood teachers perceive and respond to young children’s challenging behaviour in Western Australia’s Kindergarten to Year 2 settings. The research was grounded in Attachment Theory and Ecological Systems Theory, highlighting the relational and environmental factors influencing teacher …

Return Serve: Exploring The Dialogism Of The Australia-China Relationship In Media Coverage Between 2020-2022, Jordan Hogan

Theses: Doctorates and Masters

Australia and the People’s Republic of China (PRC) have a dynamic bilateral relationship that is defined by interdependency and mutual political scepticism. This thesis provides an analysis of Australian and Chinese news media perspectives on this relationship. Via an in-depth examination of opinion pieces from national press, I map the significant developments of a period of deteriorating relations between 2020 and 2022. My study captures the more prominent, parochial and vitriolic media coverage of the unravelling relationship, and investigates the motivations, developments, differences, and similarities in the online publications of Australia’s national daily newspaper The Australian, and China’s Global Times. …

Transforming Urban Dynamics: Harnessing Large Language Models For Smarter Mobility, Hao Xue, Ming Jin, Shirui Pan, Flora Salim, Guansong Pang

Research Collection School Of Computing and Information Systems

Artificial intelligence (AI) has the potential to analyze mobility data and make mobility systems smarter by leveraging diverse data sources such as geospatial data, transportation logs, and real-time sensor data to optimize traffic flow, enhance public transportation systems, and support the development of autonomous vehicles. With the newly emerged generative AI paradigm, exemplified by large language models (LLMs), there is great potential to transform the current AI applications in mobility, transportation, and urban domains. This article provides an overview of recent efforts and aims to shed light on the challenges and future opportunities to facilitate the adaptation of LLMs for …

Constitutional Comparisons And Language, De Maartje Visser

Research Collection Yong Pung How School Of Law

Language can be seen as an intuitive challenge for those who embark on comparative constitutional research: its intricate entanglement with law is often overlooked and not engaged with explicitly. This chapter argues that this is a missed opportunity at best, and arguably presents a hazard for the collective quality of the scholarly discourse. It discusses four ways in which language matters when engaging in constitutional comparisons: the problem of literal translation; the problem of legal-conceptual translation; a multilingual discourse that is marked by fragmentation; and expectations in communication with a foreign or international readership. The approach taken is constructive, with …

Ai Characterisations And Their Legal Implications, Jerrold Tsin Howe Soh

Research Collection Yong Pung How School Of Law

This chapter examines the difficult legal characterisation problems that artificially intelligent systems raise and explores how different characterisations of artificial intelligence (AI) shape practical legal outcomes. Three reasons are offered for the legal difficulty with characterising AI. First, answers to characterisation problems are inherently subjective and perspective-driven, particularly when the subject is an intangible technological system. Second, AI technology is especially difficult to define since the field typically proceeds on inexact anthropomorphic metaphors. Third, AI characterisation problems raise difficult sub-problems, particularly in determining how autonomous an AI system is. The chapter thus argues that a range of plausible AI characterisations …

Attribute-Based Encryption With Searchable Encryption, Yang Yang

Research Collection School Of Computing and Information Systems

Attribute-based encryption (ABE) with searchable encryption is a notion that inherits the advantages of both ABE (Goyal et al., 2006) and searchable encryption (SE) (Boneh et al., 2004; Boneh and Waters, 2007) mechanisms to realize secure share and search for the outsourced data. ABE creates fine-grained access control system to prevent sensitive data from being accessed by unauthorized user or external attacker (Bethencourt et al., 2007). SE generates encrypted index for outsourced data such that it can be searched by a keyword trapdoor (or token) (Shi et al., 2007; Naveed et al., 2014), where the outsourced content and search keyword(s) …

An End-To-End Bi-Objective Approach To Deep Graph Partitioning, Pengcheng Wei, Yuan Fang, Zhihao Wen, Zheng Xiao, Binbin Chen

Research Collection School Of Computing and Information Systems

Graphs are ubiquitous in real-world applications, such as computation graphs and social networks. Partitioning large graphs into smaller, balanced partitions is often essential, with the biobjective graph partitioning problem aiming to minimize both the“cut” across partitions and the imbalance in partition sizes. However, existing heuristic methods face scalability challenges or overlook partition balance, leading to suboptimal results. Recent deep learning approaches, while promising, typically focus only on node-level features and lack a truly end-to-end framework, resulting in limited performance. In this paper, we introduce a novel method based on graph neural networks (GNNs) that leverages multilevel graph features and addresses …

Enhancing Electric Wheelchair Safety Via Battery State Of Charge Estimationwith Pcc–Nssr–Lstm Method, Chi Wing, Alex Tsang, Xiaoying Lu

Department of Construction, Environment and Engineering

This study explores a novel algorithm created to predict the state of charge (SOC) of batteries in electric wheelchairs (EWs) to improve EW safety by adjusting SOC thresholds and reducing consumer range anxiety. It involves collecting experimental data from lithium iron phosphate (LFP) battery cells over 1500 cycles at 25◦C, encompassing various parameters. With the Pearson correlation coefficient (PCC), a select set of key parameters including voltage, temperature, dQ/dV (capacity increase to voltage increase ratio) are chosen as inputs for non-linear state space reconstruction long short-term memory (NSSR-LSTM) neural networks, facilitating precise SOC predictions. The study showcases the precision of …

Transforming Chiller Plant Efficiency With Sc+Bas: Case Study In A Hong Kong Shopping Mall, Ming Lun, Alan Fong, Baonan Nelson Li

Department of Construction, Environment and Engineering

The imperative for building managers, in the face of high-density urban environments, is to drive existing chiller plants to greater operational efficiency through the application of advanced technological interventions. The case for applying Supervisory Control (SC) and a Building Automation System (SC+BAS) for optimizing chiller plants is the subject of investigation here, through the lens of a typical commercial shopping mall in the highdensity infrastructure of Hong Kong. The application of SC+BAS falls into the realm of advanced Trim/Respond algorithms coupled with sophisticated sequencing algorithms that allow for refined optimization of the chiller operations in response to the dynamic demands …

The Effectiveness Of Local Updates For Decentralized Learning Under Data Heterogeneity, Tongle Wu, Zhize Li, Ying Sun

Research Collection School Of Computing and Information Systems

We revisit two fundamental decentralized optimization methods, Decentralized Gradient Tracking (DGT) and Decentralized Gradient Descent (DGD), with multiple local updates. We consider two settings and demonstrate that incorporating local update steps can reduce communication complexity. Specifically, for  $\mu$-strongly convex and $L$-smooth loss functions, we proved that local DGT  achieves communication complexity {}{$\tilde{\mathcal{O}} \Big(\frac{L}{\mu(K+1)} + \frac{\delta + {}{\mu}}{\mu (1 - \rho)} + \frac{\rho }{(1 - \rho)^2} \cdot \frac{L+ \delta}{\mu}\Big)$}, where $K$ is the number of additional local update}, $\rho$ measures the network connectivity and $\delta$ measures the second-order heterogeneity of the local losses. Our results reveal the tradeoff between communication and …

Therapeutic Potential Of Brassica Carinata Microgreens Extract In Alleviating Symptoms Of Type 2 Diabetes In Wistar Rats, Lilian Nakakaawa, Ifeoluwa D. Gbala, Joel L. Bargul, Xavier Cheseto, John M. Wesonga

All Peer-Reviewed Publications

Microgreens of Brassica plants have attracted increasing research interest in the management of the prevailing epidemic of Type 2 diabetes mellitus (T2DM) because of their high nutritional value. This study evaluated the antidiabetic effects of Brassica carinata Microgreens Ethanolic Extract (BMEE) in type-2 diabetic rats. For the normoglycemic assay, rats were divided into five groups and received a single oral dose of 100, 250, and 500 mg/kg of BMEE while the control groups received distilled water and Glibenclamide. Fasting blood glucose (FBG) levels were determined on a weekly basis for 28 days in diabetic rats after treatment with BMEE at …

Governing Intelligence: Singapore’S Evolving Ai Governance Framework, Jason G. Allen, Jane Loo, Jose Luna

Research Collection Yong Pung How School Of Law

This paper provides an outline analysis of the evolving governance framework for Artificial Intelligence (AI) in Singapore. Across the Singapore government, AI solutions are being adopted in line with Singapore’s “Smart Nation Initiative” to leverage technology to make impactful changes to the nation and the economy. In tandem, Singaporean authorities have been assiduous to release a growing number of governance documents, which we analyse together to chart the city-state’s approach to AI governance in international comparison. Characteristics of Singapore’s AI governance approach include an emphasis on consensusbuilding between stakeholders (particularly government and industry but also citizens) andvoluntary or “quasi” regulation, …

Human Rights At Sea: Analyzing States' Responses To Cruise Ships During The Covid-19 Pandemic, Lixin Chen

Research Collection Yong Pung How School Of Law

In the early stages of the COVID-19 pandemic, the treatment of cruise ships by coastal states was inconsistent, with some ships being allowed to dock while others were not. To that end, this Note focuses on the obligations that a coastal state owes to the individuals onboard the cruise ships in the context of the COVID-19 pandemic, including the rights to life and health. It further considers whether and how such rights are to be balanced with other countervailing considerations of such states, such as the risk of transmission to the local communities. This author concludes with the view that …

She Speaks: Amplifying Women's Voices For Wellbeing, Narelle Lemon

Reports accepted as research outputs

Executive Summary

The SheSpeaks project successfully transformed how 223 Western Australian women understand and practice self-care, demonstrating  that targeted wellbeing literacy interventions can create lasting change  in women’s relationship with their own wellbeing. Funded by the Women’s Grants for a Stronger Future program, this innovative initiative combined evidence-based workshops with authentic podcasting to challenge the pervasive cultural narrative that positions women’s self-care as selfish  or impossible.