Digital Commons Network^™

Exploring Jvm Garbage Collector Testing With Event-Coverage, Kai Zheng, Yingquan Zhao, Junjie Chen, Hanmo You, Haoyu Wang, Haoyu Wang, Tianchang Gao

Research Collection School Of Computing and Information Systems

Garbage Collection (GC) in the Java Virtual Machine (JVM) serves as an automatic memory management mechanism, efficiently reclaiming unused memory space in different production scenarios. To optimize JVM performance, developers typically fine-tune the garbage collector by identifying an optimal set of GC configurations for specific scenarios. Despite the sophisticated design of garbage collectors, they still have the potential for bugs in different settings, and these bugs can result in more severe consequences. Hence, comprehensive testing of these garbage collectors is imperative before their release. Code coverage criteria are typically employed to assess the comprehensiveness of a test suite. However, traditional …

Zero-Shot Video Translation Via Token Warping, Haiming Zhu, Yangyang Xu, Jun Yu, Shengfeng He

Research Collection School Of Computing and Information Systems

With the revolution of generative AI, video-related tasks have been widely studied. However, current state-of-the-art video models still lag behind image models in visual quality and user control over generated content. In this paper, we introduce TokenWarping, a novel framework for temporally coherent video translation. Existing diffusion-based video editing approaches rely solely on key and value patches in self-attention to ensure temporal consistency, often sacrificing the preservation of local and structural regions. Critically, these methods overlook the significance of the query patches in achieving accurate feature aggregation and temporal coherence. In contrast, TokenWarping leverages complementary token priors by constructing temporal …

Cellscout: Visual Analytics For Mining Biomarkers In Cell State Discovery, Rui Sheng, Zelin Zang, Jiachen Wang, Yan Luo, Zixin Chen, Yan Zhou, Shaolun Ruan, Huamin Qu

Research Collection School Of Computing and Information Systems

Cell state discovery is crucial for understanding biological systems and enhancing medical outcomes. A key aspect of this process is identifying distinct biomarkers that define specific cell states. However, difficulties arise from the co-discovery process of cell states and biomarkers: biologists often use dimensionality reduction to visualize cells in a two-dimensional space. Then they usually interpret visually clustered cells as distinct states, from which they seek to identify unique biomarkers. However, this assumption is often this assumption often fails to hold due to internal inconsistencies in a cluster, making the process trial-and-error and highly uncertain. Therefore, biologists urgently need effective …

How Consistent Friendlike Conversation With Ai Companions Influences Our Attitudes And Perceptions Toward Ai: An Exploratory Experiment, Qi Hui Jerlyn Ho, Meilan Hu, Adalia Yin Hui Goh, Emma Jane Pragasam, Andree Hartanto

Research Collection School of Social Sciences

Despite skepticism and distrust in artificial intelligence (AI), it is increasingly integrated into daily life, with its potential benefits drawing interest. Yet little is known about the attitudinal and psychological effects of human–AI interactions, and whether consistent interactions with AI chatbots can change users’ attitudes and perceptions. Our within-subjects experiment (N = 52) investigated how five days of socially oriented, friendlike interactions with an AI chatbot, versus a journaling control, influenced changes in attitudes and perceptions of AI. Participants’ attitudes towards AI, trust, perceived empathy, anthropomorphism, animacy, likeability, perceived intelligence and safety, dependency, and exploratory well-being indicators were recorded. Results …

Atmospheric Circulation Reconstructions Over The Earth (Acre) 2025: Climate Data Recovery, Fiona Williamson

Research Collection College of Integrative Studies

On 15-16 September 2025, Singapore Management University hosted the annual Atmospheric Circulation Reconstructions over the Earth (ACRE, www.met-acre.net/) workshop, ’ACRE 2025: Climate Data Recovery’, chaired by Fiona Williamson, Rob Allan and Praveen Teleti. The 2-day event took place at the College of Integrative Studies and saw around 30 participants from multi-disciplinary backgrounds all working in meteorological data rescue (DaRe, www.community.wmo.int/en/data-rescue-projects-and-initiatives-dare) sharing their latest work and discoveries. Speakers were a mix of climate scientists and historians, archivists and historical climatologists from across the globe. ACRE has been operating for 18 years under Professor Rob Allan, formerly of the UK Meteorological Office …

Review Of Jungle Of Stone: The Extraordinary Journey Of John L. Stephens And Frederick Catherwood, And The Discovery Of The Lost Civilization Of The Maya, Alanis Fields

Armstrong Undergraduate Journal of History

No abstract provided.

Generalized Ramsey Numbers Of Cycles, Paths, And Hypergraphs, Deepak Bal, Patrick Bennett, Emily Heath, Shira Zerbib

Department of Mathematics Faculty Scholarship and Creative Works

Given a k -uniform hypergraph G and a set of k -uniform hypergraphs H , the generalized Ramsey number f ( G , H , q ) is the minimum number of colors needed to edge-color G so that every copy of every hypergraph H ∈ H in G receives at least q different colors. In this note we obtain bounds, some asymptotically sharp, on several generalized Ramsey numbers, when G = K n or G = K n , n and H is a set of cycles or paths, and when G = K n k and H contains …

Fiber-Reinforced Foam Concrete Using Quarry Micro Fines And Sugarcane Bagasse Ash: A Box–Behnken Design Optimization And Performance Assessment, Ravindaran Thangavel, Sanjay Kumar Shukla, Mini K. Madhavan

Research outputs 2022 to 2026

Foam concrete is well-appreciated for its thermal and acoustic benefits and is prepared by introducing foam into cement slurry/mortar. The current research examines the feasibility of Quarry Micro Fines (QMF), a waste generated from the quarries during sand manufacturing, as a substitute for fine aggregate in the preparation of foam concrete. During the preparation of concrete, a portion of cement is replaced with sugarcane bagasse ash (SCBA), while polypropylene (PP) fibers are added to improve the shrinkage resistance and tensile strength of the resulting concrete. A three-factor, three-level Box–Behnken Design (BBD) in Response Surface Methodology (RSM) was used to optimize …

Mitigating Malware Prevalence In Networks With Arbitrary Topologies: A Flip-It Cyber Game Approach Integrated With Epidemic Modeling, Mousa Tayseer Jafar, Lu Xing Yang, Gang Li, Robin Doss, Kon Mouzakis, Rajesh Vasa, Helge Janicke, Ahmed Ibrahim, Ahmed Mohsin, Iqbal H. Sarker, Kristen Moore, Seyit Camtepe, Diksha Goel

Research outputs 2022 to 2026

Cyber threats have evolved in complexity, aiming at a wide range of sectors using advanced methods and tools. This evolving threat landscape challenges existing cybersecurity frameworks, many of which lack the adaptability to counteract the complex tactics of sophisticated adversaries. Developing robust cyber defense strategies requires simulating dynamic interactions between attackers and defenders across high, moderate, and low-impact scenarios. The Flip-It cyber game serves as an intelligent framework for simulating these interactions, enabling the analysis of adaptive strategies in cybersecurity. This paper aims to address the problem of mitigating malware prevalence with full consideration of attack/defense capabilities in arbitrary network …

Flips In Two-Dimensional Hypertriangulations, Herbert Edelsbrunner, Alexey Garber, Mohadese Ghafari, Teresa Heiss, Morteza Saghafian

School of Mathematical & Statistical Sciences Faculty Publications

We study flips in hypertriangulations of planar points sets. Here a level-k hypertriangulation of n points in the plane is a subdivision induced by the projection of a k-hypersimplex, which is the convex hull of the barycenters of the (k−1)-dimensional faces of the standard (n−1)-simplex. In particular, we introduce four types of flips and prove that the level-2 hypertriangulations are connected by these flips.

Constrained Quantization For Probability Distributions, Megha Pandey, Mrinal Kanti Roychowdhury

School of Mathematical & Statistical Sciences Faculty Publications

In this work, we extend the classical framework of quantization for Borel probability measures defined on normed spaces ℝ𝑘 by introducing and analyzing the notions of the nth constrained quantization error, constrained quantization dimension, and constrained quantization coefficient. These concepts generalize the well-established nth quantization error, quantization dimension, and quantization coefficient, which are traditionally considered in the unconstrained setting and thereby broaden the scope of quantization theory. A key distinction between the unconstrained and constrained frameworks lies in the structural properties of optimal quantizers. In the unconstrained setting, if the support of P contains at least n elements, then the …

Demographic And Other Correlates Of Non-Prescription Drug Use Among College Students During The Covid-19 Pandemic, Subi Gandhi, Sidketa Fofana, Md Rafiul Islam, Tamer Oraby

School of Mathematical & Statistical Sciences Faculty Publications

Background and objectives: Substance use among college students in the U.S. remains a pressing concern and may have intensified during the COVID-19 pandemic due to increased stress, uncertainty, and academic disruptions. This study investigates the relationship between non-prescription drug use and various demographic, mental health, and behavioral factors among college students during the pandemic's early stages.

Methods: Data were collected through online and in-person surveys in the summer semester of 2021. Behavioral health was assessed using validated instruments: the Patient Health Questionnaire-9 (PHQ-9) for depression and the Drug Abuse Screening Test-20 (DAST-20) for substance use. Demographic and behavioral variables were …

A Comparative Study Of Word Embedding Techniques For Classification Of Star Ratings, Craig Mcneile, Malgorzata Wojtys, Hesham Abdelmotaleb

School of Engineering, Computing and Mathematics

Telecom services are at the core of today’s societies’ everyday needs. The availability of numerous online forums and discussion platforms enables telecom providers to improve their services by exploring the views of their customers to learn about common problems that customers face. Natural Language Processing (NLP) tools can be used to process the free text collected.One way of working with such data is to represent text as numerical vectors using one of many word embedding models based on neural networks. This research uses a novel dataset of telecom customers’ reviews to perform an extensive comparative study showing how different word …

Harmonizing Neuropsychological Test Data Across Prospective Studies, Rosita Shishegar, James D. Doecke, Yen Ying Lim, Pierrick Bourgeat, Vincent Dore, Bhargav Tallapragada, Simon M. Laws, Tenielle Porter, Samantha Burnham, Azadeh Feizpour, Ashley Gillman, Michael Weiner, Jason Hassenstab, Christopher C. Rowe, Victor L. Villemagne, Colin L. Masters, Jurgen Fripp, Hamid Sohrabi, Paul Maruff

Research outputs 2022 to 2026

Introduction: Alzheimer's disease (AD) research relies on large datasets and advanced statistical models. However, individual population studies often lack sufficient sample size for conclusive results. Harmonizing cognitive test data across studies can address this gap, despite differences in testing protocols. This study harmonizes cognitive data from three major AD cohorts to support robust clinical–pathological modelling. Methods: Information from the Alzheimer's Disease Neuroimaging Initiative (N = 1446); Australian Imaging, Biomarkers and Lifestyle (N = 1764); and Open Access Series of Imaging Studies-3 (N = 440) were integrated, including cognitive scores, demographics, genetics, and clinical and neuroimaging data. Neuropsychological tests relevant to …

Generative Artificial Intelligence In Aircraft Design Optimization, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Aircraft design optimization is essential for improving aircraft performance (such as reduced fuel consumption and lowered noise), which leads to more efficient, sustainable, and affordable aircraft. Conventional aircraft design adopts physics-based simulation models, but iteratively evaluating simulation models is computationally intensive, or even practically impossible. Meanwhile, artificial intelligence (AI) emerges as a revolutionary game changer in the modern engineering industry, including aircraft design optimization. Generative AI (genAI), one of the groundbreaking AI methods, has been advancing aircraft design optimization from various aspects, including intelligent parameterization, predictive modeling, training facilitation, and constraints handling. However, there is a lack of a review …

Machine Learning In Peak Demand Forecasting: Foundations, Trends, And Insights, Shuang Dai, Fanlin Meng, Hongsheng Dai, Qian Wang, Xizhong Chen, Wenlei Bai, Peizhi Shi, Richard Allmendinger, Yuchen Zhang, Jian Liu

Electrical and Computer Engineering Faculty Research & Creative Works

Peak demand forecasting involves predicting the maximum electricity demand within a specific period, which plays a key role in maintaining the efficiency and stability of power systems. The rapid evolution of power systems, driven by advanced metering infrastructure, local energy applications such as electric vehicles, and the increasing adoption of intermittent renewable energy, has introduced greater randomness and reduced predictability in peak demand. Given the pressing need to address more diverse implementation requirements across different contexts, accurate and reliable peak demand forecasting has become increasingly important. To the best of our knowledge, this study is the first to provide a …

Efficient Function Orchestration For Large Language Models, Xiaoxia Liu, Peng Di, Cong Li, Jun Sun, Jingyi Wang

Research Collection School Of Computing and Information Systems

Function calling is a fundamental capability of today's large language models, but sequential function calling posed efficiency problems. Recent studies have proposed to request function calls with parallelism support in order to alleviate this issue. However, they either delegate the concurrent function calls to users for execution which are conversely executed sequentially, or overlook the relations among various function calls, rending limited efficiency. This paper introduces LLMOrch, an advanced framework for automated, parallel function calling in large language models. The key principle behind LLMOrch is to identify an available processor to execute a function call while preventing any single processor …

Constrained Pricing In Logit-Based Revenue Management, Qian Shao, Tien Mai, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

We consider a dynamic pricing problem in network revenue management in which customer behavior is predicted by a choice model, that is, the multinomial logit model. The problem, even in the static setting (i.e., customer demand remains unchanged over time), is highly nonconcave in prices. Existing studies mostly rely on the observation that the objective function is concave in terms of purchasing probabilities, implying that the static pricing problem with linear constraints on purchasing probabilities can be efficiently solved. However, this approach is limited in handling constraints on prices, noting that such constraints could be highly relevant in some real …

Prisrv+: Privacy And Usability-Enhanced Wireless Service Discovery With Fast And Expressive Matchmaking Encryption, Yang Yang, Guomin Yang, Yingjiu Li, Pengfei Wu, Rui Shi, Minming Huang, Jian Weng, Hwee Hwa Pang, Deng, Robert H.

Research Collection School Of Computing and Information Systems

The evolution of decentralized identity (DID) and self-sovereign identity (SSI) frameworks, as endorsed by W3C Verifiable Credentials (VC) and eIDAS 2.0, underscores the need for secure, efficient, and privacy-preserving credential management. However, existing credential systems often depend on centralized issuers, lack efficient aggregation mechanisms, or fail to ensure unlinkability across authentication sessions. To address these challenges, we propose DISC (Decentralized Identity System with Self-Sovereign Credential Aggregation), a novel credential system that enables multi-authority credential issuance, user-controlled credential aggregation, and unlinkable authentication. DISC allows users to aggregate credentials from multiple issuers while maintaining constant-size authentication tokens and supporting batch verification for …

Prompt Tuning Without Labeled Samples For Zero-Shot Node Classification In Text-Attributed Graphs, Sethupathy Parameswaran, Suresh Sundaram, Yuan Fang

Research Collection School Of Computing and Information Systems

Node classification is a fundamental problem in information retrieval with many real-world applications, such as community detection in social networks, grouping articles published online and product categorization in e-commerce. Zero-shot node classification in text-attributed graphs (TAGs) presents a significant challenge, particularly due to the absence of labeled data. In this paper, we propose a novel Zero-shot Prompt Tuning (ZPT) framework to address this problem by leveraging a Universal Bimodal Conditional Generator (UBCG). Our approach begins with pre-training a graph-language model to capture both the graph structure and the associated textual descriptions of each node. Following this, a conditional generative model …

Mm-Attackg: A Multimodal Approach To Attack Graph Construction With Large Language Models, Yongheng Zhang, Xinyun Zhao, Yunshan Ma, Haokai Ma, Yingxiao Guan, Guozheng Yang, Yuliang Lu, Xiang Wang

Research Collection School Of Computing and Information Systems

Cyber Threat Intelligence (CTI) parsing aims to extract key threat information from massive data, transform it into actionable intelligence, enhance threat detection and defense efficiency, including attack graph construction, intelligence fusion, and indicator extraction. Among these research topics, Attack Graph Construction (AGC) is essential for visualizing and understanding the potential attack paths of threat events from CTI reports. Existing approaches primarily construct the attack graphs purely from the textual data to reveal the logical threat relationships between entities within the attack behavioral sequence. However, they typically overlook the specific threat information inherent in visual modalities, which preserves key threat details …

Ubiquitination Of Oncogenic Mutant P53 Via Attenuation Of Ribosome Biogenesis Machinery Effectively Inhibits Pancreatic Tumor Growth, Mudassier Ahmad, Sahir Sultan Alvi, Haider Ahsan, Carlos Perez, Vivek Kashyap, Neeraj Chauhan, Dae Joon Kim, Nirakar Sahoo, Tamer Oraby, Murali Yallapu, Subhash Chuahan, Bilal Hafeez

School of Medicine Publications

Dysregulated ribosome biogenesis and p53 mutations are known to play oncogenic roles in various cancers, including pancreatic cancer. In this study, we demonstrated the therapeutic potential of BMH-21, a pharmacologic inhibitor of RNA polymerase I, against pancreatic cancer by uncovering a novel molecular mechanism involving RPA194-mediated ubiquitination of mutant p53 without affecting the ubiquitination of wild-type p53. Our key findings are that (i) BMH-21 selectively induces apoptosis and cell growth inhibition of pancreatic cancer cells with no effect on normal human pancreatic ductal epithelial cells; (ii) BMH-21 degrades RPA194; (iii) BMH-21 inhibits recruitment of both RPA194 and RPA135 on rDNA …

Electric Dipole Forbidden, Quadrupole Allowed Transitions In The Pure Rotational Spectrum Of Cyclopropylchloromethyldifluorosilane, Alexander R. Davies, Abanob G. Hanna, Alma Lutas, Gamil A. Guirgis, S. A. Cooke, Garry S. Grubbs

Chemistry Faculty Research & Creative Works

In a recent publication, some electric dipole forbidden, quadrupole allowed ΔJ = +2 and x-type transitions were observed in the chirped-pulse Fourier transform microwave spectrum of two conformations of cyclopropylchloromethyldifluorosilane. Many of these transitions arise from a handful of mixed states and mechanisms are proposed through which these transitions become weakly allowed. Observations of electric dipole forbidden, quadrupole allowed transitions in rotational spectra are unusual for molecules which contain a chlorine nucleus owing to the small quadrupole moment of ³⁵Cl and ³⁷Cl; thus, we believe we are the first to observe x-type transitions arising from perturbations caused by …

The Case For Ai Authorship In Copyright Law, Cheng Lim Saw, Duncan Lim

Research Collection Yong Pung How School Of Law

Today, with generative AI, literary and artistic works can be created almost effortlessly. There is at present intense debate as to whether works generated by AI – broadly categorised as “AI-assisted” and “AI-generated” works – ought to attract copyright protection. AI-assisted works are those that involve some degree of human intervention. Where AI-generated works are concerned, however, such works are created autonomously by the AI itself with minimal (de minimis) input from an identifiable human being. Presently, it is generally accepted that AI-generated works do not attract copyright protection for want of a human author. This article examines whether it …

One-Step Purification Of A Bioactive Pak1-Derived Peptide, Djamali Muhoza, Emily P. Esquivel, Stacy R. Hunter, Pateince S. Okoto, Thallapuranam K.S. Kumar, Paul D. Adams

Chemistry & Biochemistry Faculty Publications and Presentations

The serine/threonine kinase PAK1 serves as a mediator of cytoskeletal reorganization and cancer-related signaling downstream of the small GTPases. Due to the challenges in purifying PAK1 complexes, a 46-residue peptide from PAK1, is widely used to study PAK1-Cdc42 signaling. Traditionally, this purification involved multi-step chromatography of recombinant GST-PBD46 complexes, yielding approximately 1 mg per 1.5 L culture. In this study, a 30 min heat treatment step after thrombin cleavage was used to precipitate GST while leaving pure PBD46 in solution. This step eliminated the need for further affinity and size-exclusion chromatography steps. This improved protocol produces proteins with a 6.5-fold …

Inflection Points In Academic Career Trajectories: Statistical Modeling And Interactive Visualization, Aicha Malouche

Theses

This thesis examines the temporal structure of academic career trajectories, with a particular focus on identifying non-linear patterns of research productivity and moments of maximum acceleration in scientific impact. Situated within the broader context of bibliometric evaluation, the study responds to long-standing limitations of aggregate and linear career models that obscure heterogeneity across disciplines and national research systems. Drawing on theories of cumulative advantage, life-cycle productivity, and structural stratification, the research seeks to clarify how and when elite researchers experience peak growth in impact over the course of their careers. The study is guided by four research questions: (1) when …

The Changing Landscape Of Pediatric Cardiology Fellowship Applications: An Update On Objective Metrics And Current Evaluation Practices, William B Kyle, Tam T Doan, James C Wilkinson

Faculty, Staff and Students Publications

The application process for medical training fellowships has evolved significantly over the last decade. Important changes in access to quantitative data, the standardized application itself, and an unprecedented shift in the interview process have forced fellowship leaders to alter their evaluation process. This study aimed to assess each of those aspects of the pediatric cardiology fellowship application process. We review the application itself, focusing on the Experiences section of the Electronic Residency Application Service (ERAS) evaluation and the Pediatric Cardiology Fellowship Evaluation Form, which accompanies each letter of recommendation (LOR). In addition to these novel analyses, we present peer-reviewed literature …

Nested Ecosystems Theory For Conceptualizing Brain Tumors, Lori A Forster, David H Gutmann

2020-Current year OA Pubs

The application of advanced multi-omic methodologies to studying brain tumors has culminated in the appreciation that these cancers function as ecosystems that depend on the interactions of a diverse collection of cell types and signals. This connectivity operates not only at the level of the cancer cell, in which variants create new growth dependencies, but also between tumor cells and the immediate tumor microenvironment, between tumor cells and cell populations residing elsewhere in the brain tissue or body, and in response to extracorporeal factors. The cellular and molecular relationships within these four interrelated strata (intracellular, extracellular, intracorporeal and extracorporeal) act …

Accelerated Diffusion Basis Spectrum Imaging With Tensor Computations, Kainen L Utt, Jacob S Blum, Donsub Rim, Sheng-Kwei Song

2020-Current year OA Pubs

This paper introduces an advanced framework for accelerated processing of diffusion-weighted imaging (DWI) data that utilizes an entire-image modeling approach to optimize the estimation of diffusion parameters from DWIs by mapping input diffusion data to predicted signals and estimating parameter values via a stochastic gradient descent optimizer (Adam). To validate this approach, we applied this framework to diffusion basis spectrum imaging (DBSI) and analyzed in vivo human brain and ex vivo mouse brain DWIs. Results demonstrate significant improvements to computational speed and signal-to-noise ratio (SNR) in estimated parameter maps compared to standard DBSI. Our approach is applicable to any diffusion …

Anxiety Gets All The Likes, Saniye Nur Ergan

Journal of Humanistic Mathematics

This internet meme (created by me:)) emerges from a simple yet persistent question that underlies much of my work: Why do we continue to treat certain emotions in mathematics as visible, nameable, and research-worthy, while others linger in the background as faint, unarticulated traces?