Digital Commons Network^™

Performance Evaluation Of Newsql Databases In A Distributed Architecture, Zhiyao Zhang, Alan @ Ali Madjelisi Megargel, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

In the last decade, application architectures have evolved drastically, moving from monolithic architectures to distributed architectures where deployment has shifted from dedicated on-premises servers to the cloud. Distributed architectures and cloud computing has enabled businesses to scale their application components across different geographical locations. While it is easy to scale the application layer, scaling its database layer that relies on traditional SQL databases is challenging and often is a common source of bottlenecks when it comes to application performance. This paper evaluates the performance characteristics between two NewSQL databases solutions, MySQL NDB Cluster vs. TIBCO ActiveSpaces IMDG. Serving as an …

Interactive Video Search With Multi-Modal Llm Video Captioning, Yu-Tong Cheng, Jiaxin Wu, Zhixin Ma, Jiangshan He, Xiao-Yong Wei, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Cross-modal representation learning is essential for interactive text-to-video search tasks. However, the representation learning is limited by the size and quality of video-caption pairs. To improve the search accuracy, we propose to enlarge the size of available video-caption pairs by leveraging multi-model LLM on video captioning. Specifically, we use LLM to generate video captions for a large video collection (i.e., WebVid dataset) and use the generated video-caption pairs to pre-train a text-to-video search model. Additionally, we use LLM to generate fine-grained captions for test video collections to enable text-to-caption retrieval. Furthermore, we build a semantic overview of the retrieved rank …

Adapting Installation Instructions In Rapidly Evolving Software Ecosystems, Haoyu Gao, Christoph Treude, Mansooreh Zahedi

Research Collection School Of Computing and Information Systems

files play an important role in providing installation-related instructions to software users and are widely used in open source software systems on platforms such as GitHub. Software projects evolve rapidly alongside their dependencies in dynamic software ecosystems, requiring frequent updates to installation instructions. These instructions are crucial for users to start with a software project. Despite their significance, there is a lack of systematic understanding regarding the documentation efforts invested in README files and the triggers behind them. To fill the research gap, we conducted a qualitative study, investigating 400 GitHub repositories with 1,163 README commits that focused on updates …

Adversarial Generative Flow Network For Solving Vehicle Routing Problems, Ni Zhang, Jingfeng Yang, Zhiguang Cao, Xu Chi

Research Collection School Of Computing and Information Systems

Recent research into solving vehicle routing problems (VRPs) has gained significant traction, particularly through the application of deep (reinforcement) learning for end-to-end solution construction. However, many current construction-based neural solvers predominantly utilize Transformer architectures, which can face scalability challenges and struggle to produce diverse solutions. To address these limitations, we introduce a novel framework beyond Transformer-based approaches, i.e., Adversarial Generative Flow Networks (AGFN). This framework integrates the generative flow network (GFlowNet)-a probabilistic model inherently adept at generating diverse solutions (routes)-with a complementary model for discriminating (or evaluating) the solutions. These models are trained alternately in an adversarial manner to improve …

Double Oracle Neural Architecture Search For Game Theoretic Deep Learning Models, Aye Phyu Phyu Aung, Xinrun Wang, Ruiyu Wang, Hau Chan, Bo An, Xiaoli Li, J. Senthilnath

Research Collection School Of Computing and Information Systems

In this paper, we propose a new approach to train deep learning models using game theory concepts including Generative Adversarial Networks (GANs) and Adversarial Training (AT) where we deploy a double-oracle framework using best response oracles. GAN is essentially a two-player zero-sum game between the generator and the discriminator. The same concept can be applied to AT with attacker and classifier as players. Training these models is challenging as a pure Nash equilibrium may not exist and even finding the mixed Nash equilibrium is difficult as training algorithms for both GAN and AT have a large-scale strategy space. Extending our …

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 …

Lara : A Light And Anti-Overfitting Retraining Approach For Unsupervised Time Series Anomaly Detection, Feiyi Chen, Zhen Qin, Mengchu Zhou, Yingying Zhang, Shuiguang Deng, Lunting Fan, Guansong Pang, Qingsong Wen

Research Collection School Of Computing and Information Systems

Most of current anomaly detection models assume that the normal pattern remains the same all the time. However, the normal patterns of web services can change dramatically and frequently over time. The model trained on old-distribution data becomes outdated and ineffective after such changes. Retraining the whole model whenever the pattern is changed is computationally expensive. Further, at the beginning of normal pattern changes, there is not enough observation data from the new distribution. Retraining a large neural network model with limited data is vulnerable to overfitting. Thus, we propose a Light Anti-overfitting Retraining Approach (LARA) based on deep variational …

Bi-Objective Dynamic Tugboat Scheduling With Speed Optimization Under Stochastic And Time-Varying Service Demands, Xiaoyang Wei, Hoong Chuin Lau, Zhe Xiao, Xiuju Fu, Xiaocai Zhang, Zheng Qin

Research Collection School Of Computing and Information Systems

With the growing emphasis on green shipping to reduce the environmental impact of maritime transportation, optimizing fuel consumption with maintaining high service quality has become critical in port operations. Ports are essential nodes in global supply chains, where tugboats play a pivotal role in the safe and efficient maneuvering of ships within constrained environments. However, existing literature lacks approaches that address tugboat scheduling under realistic operational conditions. To fill the research gap, this is the first work to propose the bi-objective dynamic tugboat scheduling problem that optimizes speed under stochastic and time-varying demands, aiming to minimize fuel consumption and manage …

Impact Of Achievement-Oriented Gamification In Erp Systems: Examining Subjective And Objective User Outcomes, E. Adeborna, Fiona Fui-Hoon Nah, L. Motiwalla

Research Collection School Of Computing and Information Systems

This research explores the effect of gamification using achievement-oriented affordances in Enterprise Resource Planning (ERP) systems on subjective (behavioral intention) and objective (performance) outcomes. Drawing on the cognitive-affectiveconative (CAC) framework, a research model was developed to explain behavioral intention and tested in a pilot experiment with 63 participants. These participants completed a post-study questionnaire for assessing the impact of gamification on users’ behavioral intention that is mediated by CAC constructs: focused immersion, enjoyment, and selfrewarding experience. Preliminary results show that gamification enhances enjoyment and self-rewarding experience, which in turn positively influence and fully mediate behavioral intention. Objective performance outcomes were …

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 …

Risk Spillover Effect Of China-Asean Supply Chains: Insights Of Industrial Transfer, Zeyang Bian, Yuning Zhang, Keng Siau, Yaqian Zhang, Jianjia He

Research Collection School Of Computing and Information Systems

As labour costs in China increase, labour-intensive industries are migrating to ASEAN countries, attracted by lower labour costs and market potential. This shift not only affects the economies of China and ASEAN but also reshapes the global manufacturing landscape. This paper investigates the correlation and spillover of supply chain risks using production exposure indicators derived from inter-country input-output data and the R-Vine Copula model. We assess the risk spillover of each country within the global supply chain. Our findings indicate that industrial relocation can significantly alter supply chain structures, thereby affecting the concentration and direction of risks. While China's role …

An Agent-Based Computational Finance Simulation Model To Study Market Efficiency, Wei Feng, Keng Siau, Wee-Yeap Lau, Lim-Thye Goh, Haonan Chen

Research Collection School Of Computing and Information Systems

The advancement of computational modeling, data systems, and digital infrastructure has enabled the rise of agent-based computational finance (ACF). This study models interactions among heterogeneous investors. By embedding behavioral logics such as environmental, social, and governance (ESG) preferences and volatility thresholds, the model captures microstructural dynamics under different trading rules. Using ACF, the authors compare transaction plus 0 day (T+0) to transaction plus 1 day (T+1). Results show that T+0 improves price discovery, deepens liquidity, and reduces transaction costs. From a computational perspective, this research contributes to ACF by showing how policy logic and investor heterogeneity can be encoded and …

More Effective Javascript Breaking Change Detection Via Dynamic Object Relation Graph, Dezhen Kong, Jiakun Liu, Chao Ni, David Lo, Lingfeng Bao

Research Collection School Of Computing and Information Systems

JavaScript libraries are characterized by their widespread use, frequent code changes, and a high tolerance for backward incompatible changes. Awareness of such breaking changes can help developers adapt to version updates and avoid negative impacts. Several tools have been targeted to or can be used to detect breaking change detection in the JavaScript community. However, these tools detect breaking changes using different ways, and there are currently no systematic reviews of these approaches. From a preliminary study on popular JavaScript libraries, we find that existing approaches, including simple regression testing, model-based testing and type differencing cannot detect many breaking changes …

Don’T Complete It! Preventing Unhelpful Code Completion For Productive And Sustainable Neural Code Completion Systems, Zhensu Sun, Xiaoning Du, Fu Song, Shangwen Wang, Mingze Ni, Li Li, David Lo

Research Collection School Of Computing and Information Systems

Currently, large pre-trained language models are widely applied in neural code completion systems. Though large code models significantly outperform their smaller counterparts, around 70% of displayed code completions from Github Copilot are not accepted by developers. Being reviewed but not accepted, their help to developer productivity is considerably limited and may conversely aggravate the workload of developers, as the code completions are automatically and actively generated in state-of-the-art code completion systems as developers type out once the service is enabled. Even worse, considering the high cost of the large code models, it is a huge waste of computing resources and …

Privacy-Preserving User Recruitment With Sensing Quality Evaluation In Mobile Crowdsensing, Jieying An, Yanbing Ren, Xinghua Li, Man Zhang, Bin Luo, Yinbin Miao, Ximeng Liu, Deng, Robert H.

Research Collection School Of Computing and Information Systems

Recruiting users in mobile crowdsensing (MCS) can make the platform obtain high-quality data to provide better services. Although the privacy leakage during the process of user recruitment has received a lot of research attention, none of the existing work considers the evaluation of the sensing quality of privacy-preserving data submitted by users, which makes the platform incapable of recruiting users suitably to obtain high-quality sensing data, thereby reducing the reliability of MCS services. To solve this problem, we first propose a sensing quality evaluation method based on the deviation and variance of sensing data. According to it, the platform can …

32nd Annual Scientific Congress Of Hong Kong College Of Cardiology Proceeding

Journal of the Hong Kong College of Cardiology

No abstract provided.

10th Asian Preventive Cardiology And Cardiac Rehabilitation Conference

Journal of the Hong Kong College of Cardiology

No abstract provided.

First In The Field: Pioneering In Structural Heart Interventional Echocardiography, Alex Pui-Wai Lee

Journal of the Hong Kong College of Cardiology

Structural heart disease (SHD) has emerged as one of the most dynamic frontiers in contemporary cardiology. Interventional echocardiography, once a niche discipline, is now central to the planning, execution, and follow-up of complex structural interventions. This comprehensive review traces the evolution of the field, anchored in both scientific literature and firsthand experience. We explore the journey from 2D to 3D imaging, the impact of mentorship and research at the Mayo Clinic, the rise of advanced interventional devices, the integration of artificial intelligence and robotics, and the importance of resilience and teamwork. Our aim is to inspire, inform, and chart a …

Salinity Controls On Steel Biocorrosion Relevant To The Disposal Of High-Level Radioactive Waste, M. N. Rose, C. Boothman, S. Shaw, K. Morris, D. L. Engelberg, M. T. Bailey, J. R. Lloyd

School of Geography, Earth and Environmental Sciences

In a geological disposal facility (GDF) for spent fuel and high-level radioactive waste, the canister serves as one of the main engineered barriers. The resistance of the canister to degradation processes such as microbially influenced corrosion (MIC) needs be characterised to support GDF environmental safety cases. Here the impacts of salinity on sulfate-reducing bacterial (SRB) activity and associated MIC were explored in 84-day batch incubations at 30 °C. A 5 % standard bentonite slurry (MX80) in a low-salinity (0.1 g l⁻¹ NaCl) artificial groundwater containing lactate added as an electron donor provided suitable conditions for the proliferation of SRB. …

Anthropogenic Microfibres And Other Microplastics In The Sediments And Soils Of A Small, Moorland Reservoir (Burrator, Southwest England), Alexandra Sutton, Andrew Turner

School of Geography, Earth and Environmental Sciences

Little is known about the sources, transport and fate of anthropogenic microfibres (AMFs) and other microplastics (MPs) in dammed reservoirs. The aim of this study was to determine the concentrations, characteristics and pathways of anthropogenic particles in sediments and soils from a small, upland reservoir (Burrator, southwest England) and its influent and effluent river. Surface and subsurface (5 cm) sediments and soils were collected and characterised for organic matter and key geochemical (Ca, Fe and Rb) and anthropogenic (Pb and Zn) elements. AMFs and MPs were isolated from samples by flotation in ZnCl₂ and analysed microscopically; a selection was …

Export Diversification And Economic Growth In Sub-Saharan Africa: Could There Be A Mixed Relationship?, Jocelyne Urielle Bedime, Julien Brice Minkande, Honoré Bidiasse

Journal of African Trade

Based on the differences in export diversification between sub-regions, this research aims to determine the type of relationship that may exist between export diversification and economic growth in Sub-Saharan Africa. Using data from 36 countries grouped according to their level of diversification, a panel ARDL model is estimated. The results show that for highly diversified sub-regions, the relationship between export diversification and economic growth is inverted U-shaped, while for concentrated sub-regions, the relationship is U-shaped. Highly diversified countries are advised to integrate further into the African continental free-trade zone, which, by lifting barriers and improving the regulatory framework, offers greater …

Ban Cookie Banners: A Case Study In Tech Regulation, Kate Klonick

Faculty Publications

Few experiences on the modern internet are as universally reviled as the cookie banner. They clutter websites with pop-ups, interrupt user flow, make information harder to access, and demand repetitive, meaningless clicks. What was once heralded as a tool to advance individual autonomy and privacy has, in practice, become a daily annoyance that breeds cynicism with the very concept of consent itself. Cookie banners do not empower; they weary. They do not inform; they obscure. They do not prevent surveillance; they normalize it.

The tragedy of the cookie banner is that it embodies the best intentions but worst solutionism of …

The Whiteness Of Wealth & Black Student Loan Debt, Renee Nicole Allen

Faculty Publications

On June 30, 2023, to the dismay of many anxious borrowers, the Supreme Court held that the Secretary of Education did not have the authority to cancel roughly $430 billion in federal student loan balances, thus blocking President Biden’s plan for student loan forgiveness. Despite authority delegated to the Secretary to waive or modify provisions of the Education Act to ensure low-to-middle income borrowers were not placed in a worse financial position because of the COVID-19 national emergency, the Court rejected the forgiveness plan and borrowers resumed payments in October 2023. Anti-Black racism in federal law and policy have contributed …

Automated Methods For Estimating Blood Alcohol Concentration Level From Facial Cues, Ensiyeh Keshtkaran

Theses: Doctorates and Masters

This thesis investigates different approaches for detecting alcohol intoxication in drivers by analysing facial video data. Tackling this issue necessitates the creation of a novel dataset to overcome the limitations of existing datasets. The dataset constructed in this study is the first to include RGB video recordings of individual faces at varying levels of alcohol intoxication during simulated driving, featuring 60 participants with BAC levels ranging from 0 to 0.165 g/100ml. The constructed dataset not only supports this thesis, but also offers the broader scientific community a valuable resource for further study and development.

Building on this, this thesis presents …

An Immanent Postfoundational Methodology For Researching The Violent Trans-Sections Of Ableism, Classism And Sexism, Elizabeth Done, Cara Baer

School of Law, Humanities and Social Sciences

This paper charts the unfolding of a small-scale qualitative study, presented at institutional ethical approval stage as drawing on posthumanist theorising and seeking to (re)configure the concept of intersectionality, and focusing on the lived experience of postgraduate students of lower socio-economic status with disabilities. The self-selected sample comprised six women, three of whom volunteered accounts of sexual violence that complicated their experiences of dis-ability and class, and highlighted the complexity of their lived experience of intersectionality. We describe a research process in which interviewing became intra-viewing, lived experience came to be understood through Deleuzian and Deleuzo-guattarian concepts and intersectionality became …

Power To Liquid And Hydrogen Use For Saf Production; A Policy And Techno-Economic Overview For Aviation​, Eva Maleviti

Publications

What is Sustainable Development: The development that meets the needs of the present without compromising the ability of future generations to meet their own needs.

1. Environmental Sustainability

2. Social Sustainability

3. Economic Sustainability

Investigation Of A Busemann Intake At Negative Angle Of Attack, Mark E. Noftz, Andrew N. Bustard, Nicholas J. Bisek, Thomas J. Juliano, Joseph S. Jewell

Publications

A high-speed, shape-transitioned, inward-turning intake was tested in Purdue’s Boeing/AFOSR Mach 6 Quiet Tunnel. The inlet model, called the Indiana Inlet (INlet), had a total contraction ratio of 4.68:1 and a design point of Mach 6 at 0° angle of attack. The model was outfitted with a suite of high-frequency pressure transducers, and the external flowfield was imaged with high-speed schlieren photography. The INlet was tested under low freestream disturbance levels for a variety of freestream unit Reynolds numbers and at-4° angle of attack. An unsteady shockwave near the leading edge of the inlet forebody, indicative of boundary layer separation, …

Artificial Intelligence And Seeing The Invisible In Arts - From The Wane Of Axiality And Symmetry To The Wax Of Invisibility And Emptiness, M. Samir Abou El-Seoud

Computer Science

Function has been always an important driver in architectural design. It is the request to generate form directly from purpose and utility. In 1896, Louis Sullivan projected that ‘form follows function’ and that the beauty of a building derives directly from its function and not from references of the built heritage. The assumption was that beauty would naturally derive from design once functional requirements are met. Thus, fitness for purpose equals beauty. In 1908, Adolf Loos even went so far as to ask for the total abandonment of decoration. In 1947, Mies van der Rohe made his paradigm shift, function …

Pre-Programmable Directional Stiffness In Continuum Robotic Arms: Effects Of Truss Configurations, Mostafa Abdelaziz, Zahy Elgendy, Mahmoud Magdy

Mechanical Engineering

This paper investigates the implementation of trussed designs in modular tendon-driven continuum arms (CAs) to address stiffness and stability limitations while maintaining adaptability. Various truss configurations— Single-Level, Combined-Level, and Alternated trusses—were analyzed using Finite Element Analysis (FEA) to evaluate their impact on flexural and axial stiffness under realistic loading conditions. Results demonstrate that truss placement significantly influences performance, with bottom-level trusses improving flexural stiffness by up to 33%, middle-level trusses enhancing axial stiffness by 43%. Further, Combined-Level configurations provide superior overall stiffness, with MiddleBottom trusses achieving a 66.5% improvement in flexural stiffness and a 70.9% increase in axial stiffness, while …

A Refined Dual-Valued Neutrosophic Copras-Based Approach For Holistic Evaluation Of English Teaching Standards, Peng Tong, Bin Xie

Neutrosophic Sets and Systems

The evaluation of college English teaching (CET) quality helps to improve teaching standards, ensure the achievement of teaching objectives, and enhance students' language skills and overall competence. Through feedback from evaluations, teachers can refine their teaching methods, optimize course design, and meet students' needs. Additionally, teaching quality evaluation promotes the professional development of teachers, facilitates the rational allocation of educational resources, and ensures effective teaching outcomes. The evaluation of CET quality in vocational colleges in the new era involves the multiple-attribute decision-making (MADM) process. Currently, COPRAS methods are employed to address Multi-Attribute Decision-Making (MADM) challenges. To handle uncertain data in …