Digital Commons Network^™

Mando-Llm: Heterogeneous Graph Transformers With Large Language Models For Smart Contract Vulnerability Detection, Nhat Minh Nguyen, Huu Hoang Nguyen, Long Le Thanh, Zahra Ahmadi, Thanh Nam Doan, Daoyuan Wu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Detecting vulnerabilities in smart contracts is vital for the security and reliability of decentralized apps. To facilitate vulnerability detection, contract codes, including bug patterns, are represented as heterogeneous graphs with various nodes and edges, like control-flow and function-call graphs. However, existing graph learning techniques struggle with large, complex graphs. This paper presents MANDO-LLM, a novel framework that combines heterogeneous graph transformers (HGTs) with large language models (LLMs) for detecting vulnerabilities in smart contracts represented as heterogeneous contract graphs built upon control-flow and call graphs. MANDO-LLM uses LLMs to capture code features from control-flow and call data, customizes HGTs to learn …

Stableguard: Towards Unified Copyright Protection And Tamper Localization In Latent Diffusion Models, Haoxin Yang, Bangzhen Liu, Xuemiao Xu, Cheng Xu, Yuyang Yu, Zikai Huang, Yi Wang, Shengfeng He

Research Collection School Of Computing and Information Systems

The advancement of diffusion models has enhanced the realism of AI-generated content but also raised concerns about misuse, necessitating robust copyright protection and tampering localization. Although recent methods have made progress toward unified solutions, their reliance on post hoc processing introduces considerable application inconvenience and compromises forensic reliability. We propose StableGuard, a novel framework that seamlessly integrates a binary watermark into the diffusion generation process, ensuring copyright protection and tampering localization in Latent Diffusion Models through an end-to-end design. We develop a Multiplexing Watermark VAE (MPW-VAE) by equipping a pretrained Variational Autoencoder (VAE) with a lightweight latent residual-based adapter, enabling …

Iostom: Offline Imitation Learning From Observations Via State Transition Occupancy Matching, Quang Anh Pham, Brahmanage Janaka Chathuranga Thilakarathna, Tien Mai, Akshat Kumar

Research Collection School Of Computing and Information Systems

Offline Learning from Observations (LfO) focuses on enabling agents to imitate expert behavior using datasets that contain only expert state trajectories and separate transition data with suboptimal actions. This setting is both practical and critical in real-world scenarios where direct environment interaction or access to expert action labels is costly, risky, or infeasible. Most existing LfO methods attempt to solve this problem through state or state-action occupancy matching. They typically rely on pretraining a discriminator to differentiate between expert and non-expert states, which could introduce errors and instability—especially when the discriminator is poorly trained. While recent discriminator-free methods have emerged, …

Misodice: Multi-Agent Imitation From Mixed-Quality Demonstrations, The Viet Bui, Tien Mai, Hong Thanh Nguyen

Research Collection School Of Computing and Information Systems

We study offline imitation learning (IL) in cooperative multi-agent settings, where demonstrations have unlabeled mixed quality - containing both expert and suboptimal trajectories. Our proposed solution is structured in two stages: trajectory labeling and multi-agent imitation learning, designed jointly to enable effective learning from heterogeneous, unlabeled data. In the first stage, we combine advances in large language models and preference-based reinforcement learning to construct a progressive labeling pipeline that distinguishes expert-quality trajectories. In the second stage, we introduce MisoDICE, a novel multi-agent IL algorithm that leverages these labels to learn robust policies while addressing the computational complexity of large joint …

Rising From Ashes: Generalized Federated Learning Via Dynamic Parameter Reset, Jiahao Wu, Ming Hu, Yanxin Yang, Xiaofei Xie, Zekai Chen, Chenyu Song, Mingsong Chen

Research Collection School Of Computing and Information Systems

Although Federated Learning (FL) is promising for privacy-preserving collaborative model training, it suffers from low inference performance due to heterogeneous client data. Due to heterogeneous data across clients, FL training easily learns client-specific overfitting features. Existing FL methods adopt coarsegrained averaging, which can easily cause the global model to get stuck in local optima, leading to poor generalization. Specifically, this paper presents a novel FL framework, FedPhoenix, to address this issue. It stochastically resets partial parameters in each round to destroy some features of the global model, guiding FL training to learn multiple generalized features for inference rather than specific …

Sempo: Lightweight Foundation Models For Time Series Forecasting, Hui He, Kun Yi, Yuanchi Ma, Qi Zhang, Zhengdong Niu, Guansong Pang

Research Collection School Of Computing and Information Systems

The recent boom of large pre-trained models witnesses remarkable success in developing foundation models (FMs) for time series forecasting. Despite impressive performance across diverse downstream forecasting tasks, existing time series FMs possess massive network architectures and require substantial pre-training on large-scale datasets, which significantly hinders their deployment in resource-constrained environments. In response to this growing tension between versatility and affordability, we propose SEMPO, a novel lightweight foundation model that requires pretraining on relatively small-scale data, yet exhibits strong general time series forecasting. Concretely, SEMPO comprises two key modules: 1) energy-aware SpEctral decomposition module, that substantially improves the utilization of pre-training …

A Rate-Dependent Coreset Selector For Continual Learning On Time-Varying Data Distributions, Zilin Luo, Zichen Tian, Yaoyao Liu, Qianru Sun

Research Collection School Of Computing and Information Systems

In this paper we review the concept of “phase” defined in Class-Incremental Learning (CIL), i.e., learning new classes while not forgetting old ones. Due to this design, classic CIL algorithms are mostly offline or can handle only intensive data distribution shifts across the phases. However, real-world data streams are often online, usually with uncertain or untraceable changes in their data distributions. To this end, we design the per-step distribution shifts by modeling the class sampling weights using bell-shaped curves. Such a design respects the rise-and-fall nature and presents realistic but underexplored challenges for CIL: 1) The data non-stationarity across steps …

Reliable-Data-Split (Rds): Maximizing Model Potential With Reinforced Selection Strategy, Hoang D. Nguyen, Xuan-Son Vu, Quoc Tuan Truong, Duc-Trong Le

Research Collection School Of Computing and Information Systems

The nexus between data characteristics and parametric models is fundamental for developing effective and reliable artificial intelligence (AI) systems. Mismatches in data properties for model development may lead to deleterious effects on AI model performance in machine learning practice. This paper proposes a Reliable Data Split (RDS) procedure to learn how to select data points that will generalise the target domain adequately by employing prior knowledge of the data generative process. We introduce a reinforced selection strategy using deep reinforcement learning with diverse black box predictors in maximising ensemble rewards as the proxy of model performance potential while maintaining an …

Digital Communications Between Firms And Investors: Impact Of Explanatory Responses On Investor Engagement In Online Financial Q&A, Runyu Wang, Zili Zhang, Keng Siau, Ziqiong Zhang

Research Collection School Of Computing and Information Systems

The emerging trend of digital communications between firms and investors through online question-and-answer (Q&A) platforms is recognized as a vital strategy for managing investor relations, contributing to enhanced market efficiency and information transparency through increased information exchange. Potential investors can seek responses from firm managers to address their information needs, thereby mitigating market uncertainties. To provide foundational insights, we conduct a survey of investors to assess their awareness, usage, and perceptions of firm-investor Q&A platforms. In the subsequent empirical study, we specifically focus on the substance of managers’ responses, which are primarily aimed at clarifying firm events or information. In …

Imprisonment When An Offender Cannot Pay A Fine, Benjamin Joshua Ong

Research Collection Yong Pung How School Of Law

According to a common-law rule in place since the 1993 case of Low Meng Chay v Public Prosecutor [1993] 1 SLR(R) 46, if the court is minded to impose a fine but the offender will clearly be unable to pay a fine, the offender should be sentenced to imprisonment instead (as opposed to a fine coupled with a default imprisonment term). While one can understand why the courts may apply this practice, the practice obscures the crucial distinction between: (a) being sentenced to a fine, then imprisoned in default of payment (which, it is submitted, is the correct course of …

Copyright Ownership And Duration Of Ai-Authored Works, Cheng Lim Saw

Research Collection Yong Pung How School Of Law

On the assumption that Parliament has endorsed the notion of AI authorship and the prospect that copyright may well subsist in works created autonomously by the AI itself, this essay further explores allied issues surrounding the ownership and duration of copyright in AI-authored works.

Characterization Of Water Intake And Water Conversion Ratio For Male And Female Broilers From Four Commercial Broiler Lines Reared To Eight Weeks Of Age, J.Z. Hiltz, C.W. Maynard, T.W. Tabler, M.A. Maquesda, K.M. Shafer, K.B. Nelson, M.T. Kidd, N.B. Anthony, S.K. Orlowski-Workman

Poultry Science Faculty Publications and Presentations

Increased interest and investigation into the sustainability of broiler production has led to a need for reliable and repeatable means to measure water intake and its conversion rate into salable meat. Therefore, a study was conducted to characterize the water intake and water conversion ratio (WCR) of male and female broilers from four modern broiler strains. Two of these lines represented fast growing broiler strains (FGB A and FGB B) targeting a small bird market and two represented high yielding broiler strains (HYB A and HYB B). Three replicates of 25 sexed broilers from each line were placed into 24 …

A Protectorate Divided: The Otjimbingue Petition And Settler Contestations Of Railway Construction In German Southwest Africa, 1897–1902, Marta Millar

Publications and Research

Supporters of the State Railway in German Southwest Africa heralded its construction as ‘the dawn of a new era for the protectorate’ (Windhoeker Anzeiger, 27 October 1898). While railways did enable the expansion of colonial communities, not all settlers wrote as optimistically about this change as did the Anzeiger’s editor. Between 1897 and 1902, familial correspondence and debates in the protectorate’s first newspaper, the Windhoeker Anzeiger, reveal how various settlers negotiated the railroad’s transformative impact on colonial society and their everyday lives. Opposition voices argued that the railroad would harm the fragile colonial economy, serving only …

Cv: Sarah Drake Brown (Secondary Education, Elementary Education/Special Education), Sarah Drake Brown

Education Department Faculty Curricula Vitae

No abstract provided.

Digital Commons Statistics For December 2025, Liberty University

Digital Commons Statistics

No abstract provided.

American Institute Of Accountants War Program, American Institute Of Accountants

Journal of Accountancy

No abstract provided.

Engage, Assess, Intervene, Evaluate: Barriers Facing The Elderly Population, Isabel Anderson, Gracie Brown, Mari Langton

Student Projects

This study examined barriers faced by older adults in Orange City, Iowa, through a mixed-methods community practice project incorporating assessment, implementation, and evaluation. During the assessment phase, researchers conducted interviews with elderly residents and professionals, gathered observational data, and facilitated community dialogue using the Nominal Group Technique. Key themes included social isolation, transportation challenges, financial strain, limited health literacy, and difficulty transitioning from independence to assisted living. A strong cultural emphasis on independence often discouraged help-seeking, while fragmented agency communication and rural limitations in specialized care further complicated service navigation. Asset mapping and power analysis highlighted community cohesion, faith-based support, …

Backdoorllm: A Comprehensive Benchmark For Backdoor Attacks And Defenses On Large Language Models, Yige Li, Hanxun Huang, Yunhan Zhao, Xingjun Ma, Jun Sun

Research Collection School Of Computing and Information Systems

Generative large language models (LLMs) have achieved state-of-the-art results on a wide range of tasks, yet they remain susceptible to backdoor attacks: carefully crafted triggers in the input can manipulate the model to produce adversaryspecified outputs. While prior research has predominantly focused on backdoor risks in vision and classification settings, the vulnerability of LLMs in open-ended text generation remains underexplored. To fill this gap, we introduce BackdoorLLM1 , the first comprehensive benchmark for systematically evaluating backdoor threats in text-generation LLMs. BackdoorLLM provides: (i) a unified repository of benchmarks with a standardized training and evaluation pipeline; (ii) a diverse suite of …

Safe-Sora: Safe Text-To-Video Generation Via Graphical Watermarking, Zihan Su, Xuerui Qiu, Hongbin Xu, Tangyu Jiang, Jun-Hao Zhuang, Chun Yuan, Ming Li, Shengfeng He, Fei Yu

Research Collection School Of Computing and Information Systems

The explosive growth of generative video models has amplified the demand for reliable copyright preservation of AI-generated content. Despite its popularity in image synthesis, invisible generative watermarking remains largely underexplored in video generation. To address this gap, we propose Safe-Sora, the first framework to embed graphical watermarks directly into the video generation process. Motivated by the observation that watermarking performance is closely tied to the visual similarity between the watermark and cover content, we introduce a hierarchical coarse-to-fine adaptive matching mechanism. Specifically, the watermark image is divided into patches, each assigned to the most visually similar video frame, and further …

Efskip: A New Error Feedback With Linear Speedup For Compressed Federated Learning With Arbitrary Data Heterogeneity, Hongyan Bao, Pengwen Chen, Ying Sun, Zhize Li

Research Collection School Of Computing and Information Systems

Due to the communication bottleneck in distributed and decentralized federated learning applications, algorithms using compressed communication have attracted significant attention. The Error Feedback (EF) is a widely-studied compression framework for convergence with biased compressors such as top-k sparsification. Although various improvements have been obtained in recent years, the theoretical guarantee for EF-type framework is still limited. Previous works either 1) rely on strong assumptions such as bounded gradient/dissimilarity assumptions, thus can not deal with arbitrary data heterogeneity and also slow the convergence speed, or 2) can not enjoy linear speedup in the number of clients. In this work, we propose …

Generalization Bounds For Rank‑Sparse Neural Networks, Antoine Ledent, Rodrigo Alves, Yunwen Lei

Research Collection School Of Computing and Information Systems

It has been recently observed in much of the literature that neural networks exhibit a bottleneck rank property: for larger depths, the activation and weights of neural networks trained with gradient-based methods tend to be of approximately low rank. In fact, the rank of the activations of each layer converges to a fixed value referred to as the “bottleneck rank”, which is the minimum rank required to represent the training data. This perspective is in line with the observation that regularizing linear networks (without activations) with weight decay is equivalent to minimizing the Schatten p quasi norm of the neural …

Framerate Sensitivity And Cinemagoing Explain The Soap Opera Effect Of Films: A Preregistered Study Of Undergraduate Students In Singapore., Sonny Rosenthal, Benjamin J. Li

Research Collection College of Integrative Studies

The soap opera effect is an unsettling feeling that some individuals experience while watching films at a high framerate. It has received little scholarly attention, and most explanations of it are speculative or anecdotal. Drawing on the mere exposure effect, this preregistered laboratory experiment provides new evidence of framerate sensitivity and cinemagoing as explanatory factors of the soap opera effect. Undergraduate students (N = 270) reported their cinemagoing and completed a novel task to measure their framerate sensitivity. They also completed a task indicating their framerate preferences. Those with a higher framerate sensitivity and more regular cinemagoing preferred the standard …

Novice Instructors Can Make Satisfying Video Lectures By Using Familiar Techniques: A Repeated-Measures Test Of Video Lecture Formats And Learner Satisfaction Theory, Sonny Rosenthal, Stuart Braiman, Dawn Z. Y. Poh

Research Collection College of Integrative Studies

Research has shown that composite video lectures lead to higher learner satisfaction than other video lecture formats, but this finding has not been replicated among novice instructors. In this study, six PhD students created two video lectures on different topics. One used the picture-in-picture (PiP) format, while the other used the video composite format. Undergraduate student participants (N = 185) watched both video lectures by a single instructor and rated them on several variables. Contradicting prior research, the participants rated the composite video as having lower content quality (Cohen’s d = -0.35) and instructor-content interaction (Cohen’s d = -0.17) than …

Navigating Ai-Nature Frictions: Autonomous Vehicle Testing And Nature-Based Constraints, Prerona Das, Orlando Woods, Lily Kong

Research Collection College of Integrative Studies

In cities, the application of Artificial Intelligence (AI) is being directed towards transforming different aspects of urban life. These applications take material form in urban spaces, with autonomous vehicles (AVs) providing a prominent example. AI systems rely on large volumes of data on their surroundings to refine the algorithms and enhance the accuracy of prediction for operational efficiency and safety. However, such algorithmic learning and execution can present challenges when dealing with the unpredictable, complex, and dynamic aspects of urban spaces. Nature is a paradigmatic example of such unpredictability, because natural phenomena usually defy consistent patterns and precise data-based modelling. …

Privately Owned Companies Dominate Renewable Energy Generation Ownership Around The World, Dyaran Bansraj, Theodor Florian Cojoianu, Xi Hu, Khaladdin Rzayev, Francisco Urzua

Research Collection College of Integrative Studies

Global sustainable finance policies are premised on publicly listed companies driving decarbonization through transparency, investor pressure, and capital market access. Analysing c. 20,000 corporate owners of renewable and fossil-fuel assets worldwide, we show the opposite: private firms own approximately 75% of global renewable generation capacity. This private dominance holds across all major technologies and regions, with listed ownership of renewable assets being the majority only in the oil & gas and technology sectors. The Paris Agreement did not alter this balance. Instead, ownership of the energy transition reflects countries' financial structures, with similar patterns observed across manufacturing, construction, and financial …

Bim-To-Brick: Using Graph Modeling For Iot/Bms And Spatial Semantic Data Interoperability Within Digital Data Models Of Buildings, Filippo Vittori, Fu Chuan Tan, Laura Anna Pisello, Adrian Chong, Cristina Piselli, Clayton Miller

Research Collection College of Integrative Studies

The holistic management of a building requires data from heterogeneous sources such as building management systems (BMS), Internet-of-Things (IoT) sensor networks, and building information models (BIM), all aimed at environmental well-being. Data interoperability is a key component to eliminate silos of information, and using semantic web technologies like the BRICK schema, an effort to standardize semantic descriptions of the physical, logical, and virtual assets in buildings and the relationships between them, is a suitable approach. However, current data integration processes can involve significant manual interventions. This paper presents a methodology to automatically collect, assemble, and integrate information from a building …

Cross-Domain Disaggregation Of Electricity For Heating In All-Electric School Buildings – Learning From School Buildings With District Heating, Synne Krekling Lien, Ada Canaydin, Clayton Miller, Chun Fu, Hussain Kazmi, Jayaprakash Rajasekharan

Research Collection College of Integrative Studies

Electric heating is widespread in Norwegian buildings and significantly contributes to peak loads in the electricity grid. Non-residential buildings are typically heated either by district heating or a combination of electrical heating appliances. Despite its widespread use, most buildings lack sub-meters for electric heating. As a result, the true potential for energy efficiency and load flexibility from heating appliances in buildings remains unknown. Non-intrusive load monitoring and disaggregation techniques offer alternatives to sub-metering by using data-driven methods to extract electricity use for appliances from time-series data. However, little research has been conducted on disaggregating electrical heating loads from low-resolution data, …

The Pluralistic Natural Capital Values Of A Tropical City, Adrienne Gret-Regamey, Et Al.

Research Collection College of Integrative Studies

Nature in cities is essential for human well-being. Quantifying and valuing the goods and services provided by nature to city dwellers is missing in tropical contexts. Yet, as cities worldwide face similar challenges, understanding the services provided by tropical urban ecosystems becomes imperative for effective management. Here, we present the first Natural Capital Assessment of a tropical city, unveiling three critical insights. Firstly, we demonstrate the vital reliance of a developed tropical city on nature, particularly for climate change mitigation through regulating services. Secondly, we identify intact natural areas as Singapore’s most valuable assets, stressing the significance of the quality …

Energy Flow Differences In Throwing Arm Joints Between Javelin And Weighted Balls In Male Javelin Throwers, Hans-Peter Köhler, Kristof Kipp, Nikola Prvulović, Maren Witt

Exercise Science Faculty Research and Publications

Introduction: To enhance release velocity during competition, javelin throwers incorporate implements of varying mass into their training regimens. Previous research has demonstrated that, although velocity contributes quadratically to the computation of kinetic energy, heavier implements generate substantially greater kinetic energy at the moment of release, despite markedly lower release velocities. The primary objective of the present investigation was to analyze energy transfer within the throwing arm to gain deeper insight into the biomechanical mechanisms underlying the use of implements with different masses.

Methods: The three-dimensional coordinates of 16 reflective markers were recorded for 6 athletes during throws using 6 different …

Tips On The Prisma Flow Diagram & Methods Section Write-Up, Sandra Y. Desjardins, Jenny Stockton

TMC Library Newsletter (2015-)

Clearly communicate your research methodology with a well-crafted PRISMA flow diagram. This 30-minute class provides practical tips and a step-by-step guide to creating a clear and informative methods section for your research papers. Related LibGuide: Where to Publish Your Research by Tracy Ashby. Come learn the foundational skills needed for successful research in a welcoming and practical "Lunch & Learn" environment. Register here to attend the session.