Digital Commons Network^™

The City As Showroom: Singapore And The Rise Of The "Urban Solutions" Industry, Sol Andrew Stokols

Research Collection College of Integrative Studies

This article uses the concept of the “city as showroom” to describe an emergent logic shaping urban development that stems from the growing importance of “urban solutions” as an industry. Focusing primarily on Singapore, the article examines how certain urban districts and high-profile sites are conceptualized as “showrooms” for the infrastructure and urban technologies they aim to export around the world. The idea of the “city as showroom” combines aspects of the curation of a city’s image through showcase districts, as well as “testbed urbanism” seen in certain smart-city projects. Singapore's need to reproduce itself as a model of urban …

Potential Recyclable Materials In Buildings: A Framework For Greenhouse Gas Emissions Assessment Of Residential Buildings In Singapore, Pradeep Alva, Riccardo Talami, Wanyu Pei, Goran Sibenik, Martin Mosteiro-Romero, Clayton Miller, Rudi Stouffs

Research Collection College of Integrative Studies

As countries aim to reduce resource consumption and greenhouse gas (GHG) emissions, Whole Life Carbon Assessment (WLCA) has become a vital method for quantifying embodied and operational GHG emissions. However, few studies have conducted WLCA on an urban scale, often addressing operational or embodied GHG emissions in isolation without considering their cumulative impact. This study introduces a city-wide WLCA framework to assess the potential recyclable materials of urban building stock, using Singapore as a case study with 5915 public residential buildings. Upfront GHG emissions are calculated from material intensity and building information, while operational emissions are based on energy use …

Screening Tools For Maternal Mental Health In Africa: A Systematic Review, Joyce Jebet, Irene Mageto, Benard Mutwiri, Abednego Ongeso, Ruth Wagathu, Rose Maina, Denis Munene, Kawira Kithuci, Peter Gatiti

School of Nursing & Midwifery, East Africa

Background:

Maternal health during pregnancy and the postnatal period encompasses mental health, which is a key aspect in enhancing a positive outcome. Despite screening for other possible complications during pregnancy and the postnatal period, very little attention has been paid to screening for mental health. Screening is a key tool in early diagnosis and, eventually, timely diagnosis and management in cases where complications arise.

Aim:

This study aimed to assess the available maternal mental health screening tools and compare the outcome on their utilization during pregnancy and postnatal periods in the African continent.

Methodology:

This was a …

Imaginatively Humankind Dwells: The Necessity Of The Imagination For Divine-Human Commun(E)Ication, Tracey-Ann Pypker-Van Brenk

Pro Rege

No abstract provided.

But What Did I Really Know?, James C. Schaap

Pro Rege

No abstract provided.

Co-Editors’ Corner, Raven Jones, Tanya Upthegrove Gregory, Alexandra Sánchez

Language Arts Journal of Michigan

No abstract provided.

Bayesian Optimization Of Laser Wakefield Acceleration Via Spectral Pulse Shaping, B. Z. Djordjević, C. Benedetti, Asa D. Mcnaughton, R. Lehe, H.-E. Tsai, S. C. Wilks, B. A. Reagan, G. J. Williams, J. Van Tilborg, C. B. Schroeder

Physics Faculty Publications and Presentations

In this paper, we investigate the effect of spectral pulse shaping of the laser driver on the performance of channel-guided, laser–plasma accelerators. The study was carried out with the assistance of Bayesian optimization using particle-in-cell simulations. We used a realistic plasma profile based on a novel optical-field-ionized channel technique with ionization injection and low, on-axis plasma densities to maximize the energy gain of the electron bunch trailing the laser. Spectral shaping allows us to modify the temporal profile of the laser driver while keeping the laser energy constant, affecting the acceleration and injection processes. In addition, we consider how modifying …

Artificial Personhood: The Implications Of Recognizing The Legal Personhood Of Artificialintelligence, Daniel C. Borges

Vanderbilt Journal of Entertainment & Technology Law

Artificial intelligence (AI) is here in a big way. As society grapples with the implications of this profound new technology, the question of whether AI entities should be granted independent legal recognition, akin to human personhood, has emerged as a pivotal topic in jurisprudence. This Article explores the foundations, evolution, and implications of AI personhood, addressing philosophical perspectives, the development of personhood as a legal fiction (with specific emphasis on corporate personhood), and the need for AI personhood to counter the risks posed by rapidly developing AI technology. It defines the "AI person" as one whose legal recognition furthers a …

Who's Afraid Of Copyright And Ai?, Deborah R. Gerhardt

Vanderbilt Journal of Entertainment & Technology Law

Copyright and AI need not be a copyright no man’s land. Recent decisions by the Copyright Office have gotten so much media attention that many creators are unsure if they can secure copyright protection if they use AI as a creative tool. The proposed creative control paradigm can help us all tackle the challenge of determining when works created with the assistance of AI are copyrightable. Instead of relying on long-established nuanced precedent for protecting works generated with new technology, the Copyright Office asserts that any content generated with assistance from AI tools is unprotectable. This position is radically inconsistent …

Open Secrets, Robin Feldman Distinguished Professor Of Law, Vaughn Goehrig -- Center For Innovation

Vanderbilt Journal of Entertainment & Technology Law

Patents and trade secrets were never intended to meet, but in the world of biologic drugs, they’ve become as thick as thieves. Patent law’s disclosure requirement has demanded far too little of biologics manufacturers—allowing them to keep vital manufacturing details under trade secret lock and key. This intellectual property patchwork has been devastating for drug affordability: Because the most critical manufacturing information remains hidden, makers of follow-on biologics (called biosimilars) are often stuck reinventing the wheel, even after the original patents have expired. This Article makes two principal contributions to illuminating this problem. First, it presents, for the first time …

Exploring The Role Of Vitamin D In Familial Mediterranean Fever: Pathogenesis, Triggers, And Immune Modulation, Hagop Sassounian, Saad Aad, Hilda E. Ghadieh, Lara Khouzami, Elsa Nicolas, Sami Azar, Frederic Harb

All Works

Familial Mediterranean Fever (FMF) is among the most frequent autoinflammatory diseases in populations originating from the area of Middle Eastern and Mediterranean countries. It is caused by mutations in the MEFV gene, which causes dysregulated pyrin expression and thus an immunologic anomaly. FMF is diagnosed by recurrent episodes of fever and serosal inflammation, predominantly peritonitis and pleuritis, as well as other systemic symptoms. Recent research is dedicated to searching for factors beyond genetic code contributing to how FMF evolves, the severity of its symptoms and response to conventional therapy—colchicine. These factors include epigenetic modifications of the MEFV gene and other …

Digital Advertising Regulation And Consumer Protection Policy In The Uae: Ethical Challenges And Consumer Trust In The Digital Era, Harith Yas, Wided Dafri, Basma Kashmoola, Maytha Al-Ali, Omnia Salem, Ahmed Almufti

All Works

It is remarkable that the current research primarily aims to measure the extent to which UAE Consumers use various Digital Advertising Channels, as well as to evaluate e-marketing requirements and the degree of compliance in the United Arab Emirates. The Research, however, has employed a Descriptive-Analytical Approach, collecting data through a questionnaire that includes several questions targeting a sample of 150 consumers from different Emirates. The data were analyzed using SPSS and statistical method s, including complaint analysis, Interest Frequencies, and graphical representations. Our results show that social media is the most widely used digital advertising channel, accounting for 34% …

A Machine Learning Framework For Residential District Cooling: Forecasting Consumption, Explaining Drivers, And Evaluating Decarbonization Pathways, Kadhim Hayawi, Husna Maliakkal, Neethu Venugopal, Thanveer Musthafa Hussain, Gomathi Bhavani Rajagopalan

All Works

District Cooling Systems (DCS) in the Middle East, while energy-efficient, are significant contributors to carbon emissions. This study introduces a novel framework to decarbonize DCS operations by integrating predictive machine learning, explainable AI (XAI), and renewable energy planning, all grounded in extensive real-world data. Leveraging a unique dataset from 59 residential buildings in the UAE—including energy consumption, climate variables, and building features—we developed a high-fidelity cooling load forecasting model. Following a rigorous chronological validation methodology, the Random Forest model was identified as the most robust, achieving a strong performance (R² = 0.8256, RMSE = 11,668.31). Outdoor temperature was confirmed …

The Can Challenge: Understanding The Best Ways To Incentivise Recycling Through A Diffusion Approach, Michael Brock, Lucia M. Murgia, Stefania Sitzia, Jiwei Zheng

All Works

Understanding the best ways to incentivise recycling and improve the efficiency of waste practices is a key environmental, social, and economic management problem that needs addressing.We search for solutions to this issue by testing the effectiveness of two incentive mechanisms (a piece-rate and a lottery-based systems). We run a similar field experiment in three different locations, namely a student, residential and workplace environment, to verify the robustness of our findings and thus increase confidence in the external validity of our intervention. By interpreting recycling activity as marketable service, we employ a diffusion model to analyse the potential adoption of the …

From Ethical Principles To Executable Governance: A Policy-As-Code Framework For Trustworthy Ai In Higher Education, Edmund Evangelista, Syed M. Salman Bukhari

All Works

Artificial intelligence holds great potential to transform higher education, but a persistent gap remains between ethical aspirations and their practical, auditable enforcement. This study addresses that gap by developing and validating an end-to-end executable governance framework grounded in a policy-as-code (PaC) paradigm. Using student dropout prediction as a high-stakes example, the framework operationalizes governance through an automated gatekeeper, a multi-strategy fairness mitigation toolbox, and a tamper-evident audit chain for full reproducibility. The governance compliance was tested across sixteen fixed model configurations evaluated under five policy tiers (strict, medium, lenient, and two deployment-realistic variants). None were approved, as fairness violations, dominated …

The Spiritual Communities Of Bronies, Amie Sexton

Theses, Dissertations and Culminating Projects

Bronies, adult, typically male, fans of the cartoon My Little Pony: Friendship is Magic, have long been regarded for seemingly breaking expectations around gender norms. This study finds that Bronies break expectations around what is expected of spiritualism. Through interviews and ethnographic observation of social media spaces Bronies frequent, it is found that spirituality based on the cartoon within the fandom is broad, diverse, and at times, normative. A proportionally-small group of fully sincere spiritualists with plural experiences and strong convictions inspire a much larger community of post-ironic aspirants. Aspirations towards spiritual experiences and the development of profound terminologies create …

Family Planning Exemplar Country Selection Methodology: Time Lag And Trends Analysis, Zahid Memon, Abeer Mian, Ira Martopullo, Narjis Hussain, Zeba Sathar, Ali Mohammad Mir, Michael Mbizvo, Marleen Temmerman, Jen Drake, Zulfiqar Bhutta

Centre of Excellence in Women and Child Health

Introduction While many countries achieved notable gains in contraceptive use levels after the 1994 International Conference on Population and Development which redefined family planning (FP) as a human right, there was a long period of 15 years when contraceptive use levels did not receive due attention. It was only later that its subsequent inclusion in the Sustainable Development Goals and the 2012 London Summit on FP renewed global commitment and a focus towards FP. This paper aims to select countries that identify as ‘exemplar’ low-middle-income countries that have achieved exceptional progress in FP. Examining these outliers can uncover actionable drivers …

Understanding Formal Financial Access In Indonesia: Evidence From Micro Data, M. Aulia Rachman, Yozi Aulia Rahman, Maulida Dewi Pangestika, Risanda Alirastra Budiantoro

Economics and Finance in Indonesia

This study examines the determinants of access to formal financial institutions using secondary household survey data from Indonesian Family Life Survey, Wave 5 (IFLS-5). Logistic regression analysis reveals that loan amount, savings, education level, age, housing status, and internet usage are positively and significantly associated with greater access. Individuals with higher savings, higher education, and homeownership exhibit a higher probability of utilizing formal financial services. Although the significance of internet usage varies across models, it remains a strong predictor when properly controlled, particularly due to its role in enhancing digital literacy. In contrast, income and health insurance ownership do not …

Beyond The Generations: Building A High-Quality Workplace For An Age-Diverse Workforce, Cal J. Halvorsen, Bruna C. Lopez, Erika Sabbath

Brown School Faculty Publications

At a time when the U.S. is more age diverse than ever before, Americans are extending their careers for financial stability, social connection, and purpose. This article provides a brief background on the history of aging and work, from the late 1800s to present, illustrating the influence that public and organizational policies, as well as personal needs and interests, have on labor force participation. It then provides examples for how employers can create better workplaces for people of all ages, concluding with the case for why more age-inclusive workplaces lead to better results for employees, their families, and their employers.

Patchfuzz: Patch Fuzzing For Javascript Engines, Junjie Wang, Zhihua Xie, Xiaofei Xie, Xiaoning Du, Xiangwei Zhang

Research Collection School Of Computing and Information Systems

Context: Patch fuzzing is a technique aimed at identifying vulnerabilities that arise from newly patched code. While researchers have made efforts to apply patch fuzzing to testing JavaScript (JS) engines with considerable success, these efforts have been limited to using ordinary test cases or publicly available vulnerability PoCs (Proof of Concepts) as seeds, and the sustainability of these approaches is hindered by the challenges associated with automating the PoC collection. Objective: To address these limitations, we propose an end-to-end sustainable approach for JS engine patch fuzzing, named PatchFuzz. Method: It automates the collection of PoCs of a broader range of …

To Wait Or To Transfer? A Three-Level Optimization Framework For Intermodal Transfer Coordination In First Train Timetabling And Bus Bridging Services Management, Hao Li, Liujiang Kang, Norman Weik, Huijun Sun, Qingying Lai, Zhiguang Cao

Research Collection School Of Computing and Information Systems

This study addresses the integrated optimization of the first train timetabling and bus bridging service design (FTT-BBSD) for morning transfer challenges, two critical but interdependent passenger services in the public transit system. In contrast to most existing studies and conventional approaches, this study explicitly models the influence of passenger path choices and transfer mode selections on FTT-BBSD. Through a novel dual-level network representation that integrates subway and bus systems, we formulate the FTT-BBSD problem as a mixed-integer nonlinear programming model. The model simultaneously determines subway and bus timetables and bridging line deployment to minimize total travel time for all first …

A Pruning-Based Question-Answering For Interactive Video Search: A Simple Baseline, Yu Tong Cheng, Phuong Anh Nguyen, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

There are various factors affecting the performance of video search. An imprecise query will enlarge search space and reduce the discriminative power of ranking functions. This problem is further exacerbated by the presence of numerous visually or semantically similar videos in large datasets. Consequently, users need to painstakingly browse through many highly similar candidates to locate the search target, leading to increased cognitive load and inefficient searching. Ideally, engaging users through interactive questioning to resolve uncertainties in the search process is an effective strategy for progressively narrowing down the search space. However, despite rapid advances in deep learning, generating informative …

Rode: Linear Rectified Mixture Of Diverse Experts For Food Large Multi-Modal Models, Pengkun Jiao, Xinlan Wu, Bin Zhu, Jingjing Chen, Chong-Wah Ngo, Yu-Gang

Research Collection School Of Computing and Information Systems

Large Multi-modal Models (LMMs) have significantly advanced a variety of vision-language tasks. The scalability and availability of high-quality training data play a pivotal role in the success of LMMs. In the realm of food, while comprehensive food datasets such as Recipe1M offer an abundance of ingredient and recipe information, they often fall short of providing ample data for nutritional analysis. The Recipe1M+ dataset, despite offering a subset for nutritional evaluation, is limited in the scale and accuracy of nutrition information. To bridge this gap, we introduce Uni-Food, a unified food dataset that comprises over 100,000 images with various food labels, …

Benchmarking Gaslighting Negation Attacks Against Multimodal Large Language Models, Bin Zhu, Yinxuan Gui, Huiyan Qi, Jingjing Chen, Chong-Wah Ngo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Multimodal Large Language Models (MLLMs) have exhibited remarkable advancements in integrating different modalities, excelling in complex understanding and generation tasks. Despite their success, MLLMs remain vulnerable to conversational adversarial inputs. In this paper, we systematically study gaslighting negation attacks—a phenomenon where models, despite initially providing correct answers, are persuaded by user-provided negations to reverse their outputs, often fabricating justifications. We conduct extensive evaluations of state-of-the-art MLLMs across diverse benchmarks and observe substantial performance drops when negation is introduced. Notably, we introduce the first benchmark GaslightingBench, specifically designed to evaluate the vulnerability of MLLMs to negation arguments. GaslightingBench consists of multiple-choice …

Sam3-Litetext: An Anatomical Study Of The Sam3 Text Encoder For Efficient Vision-Language Segmentation, Chengxi Zeng, Yuxuan Jiang, Ge Gao, Shuai Wang, Duolikun Danier, Bin Zhu, Stevan Rudinac, David Bull, Fan Zhang

Research Collection School Of Computing and Information Systems

Vision-language segmentation models such as SAM3 enable flexible, prompt-driven visual grounding, but inherit large, general-purpose text encoders originally designed for open-ended language understanding. In practice, segmentation prompts are short, structured, and semantically constrained, leading to substantial over-provisioning in text encoder capacity and persistent computational and memory overhead. In this paper, we perform a large-scale anatomical analysis of text prompting in vision–language segmentation, covering 404,796 real prompts across multiple benchmarks. Our analysis reveals severe redundancy: most context windows are underutilized, vocabulary usage is highly sparse, and text embeddings lie on a low-dimensional manifold despite high-dimensional representations. Motivated by these findings, we …

Frozen Lvlms For Micro-Video Recommendation: A Systematic Study Of Feature Extraction And Fusion, Huatuan Sun, Yunshan Ma, Changguang Wu, Yanxin Zhang, Pengfei Wang, Xiaoyu Du

Research Collection School Of Computing and Information Systems

Frozen Large Video Language Models (LVLMs) are increasingly employed in micro-video recommendation (MVR) due to their strong multimodal understanding. However, existing apporches typically deploy LVLMs as fixed black-box feature extractors without systematically comparing alternative representation strategies. To address this gap, we present the first systematic empirical study on various feature extraction paradigms and integration strategies, along with hierarchical representations from frozen LVLMs for MVR. Extensive experiments on representative LVLMs reveal that hidden states from multiple decoder layers provide richer and more effective representations for MVR. Guided by this insight, we propose the Dual Feature Fusion (DFF) Framework, a lightweight approach …

Co-Designing With Autistic Livestreamers: Care, Constraints, And Trade-Offs In Livestreaming, Terrance Mok, Anthony Tang, Lora Oehlberg

Research Collection School Of Computing and Information Systems

Autistic livestreamers use platforms like Twitch for social connection, self-expression, and community, but these spaces also impose ongoing social and emotional demands. Prior work has documented these experiences, but less is known about what autistic creators themselves envision for the tools and platforms they use. We address this gap through a Research through Design (RtD) co-design study with three autistic Twitch streamers, using speculative artefacts as discussion prompts to explore how participants reasoned about potential livestreaming technologies. Across three co-design activities, we identify three overarching tensions shaping autistic streaming practice: Expression versus Misinterpretation and Harm; Public Participation versus Control and …

Group Conversational Agents: A Review Of Designs That Support And Shape Group Interaction, Shunyi Yeo, Tianyi Zhang, Scott Bateman, Gary Hsieh, Young-Ho Kim, Simon Tangi Perrault, Jiannan Li, Anthony Tang

Research Collection School Of Computing and Information Systems

Conversational agents that participate in or mediate group interaction introduce challenges that extend beyond supporting individual users, raising new questions about how agents participate in and influence groups. To characterise this emerging design space, we present a systematic review of 53 peer-reviewed studies on group conversational agents (GCAs). We analyse how GCAs intervene in group-level processes, including participation regulation, conflict mediation, task alignment, and execution support. Using concepts from group research as an analytic lens, we organise prior GCA work around recurring group interactional challenges (orientation, conflict, alignment, and execution), and examine the roles agents are designed to play in …

Language Embeddings Meet Shallow Autoencoders, Rodrigo Alves, Vojtěch Vančura, Pavel Kordík, Antoine Ledent

Research Collection School Of Computing and Information Systems

Shallow autoencoders are appealing recommenders due to their simplicity, scalability, and competitive retrieval quality, but they struggle in strict cold-start settings where new items have no interactions. We propose an inductive shallow autoencoder that leverages item side information (language embeddings) by fixing the decoder to item features and learning only an encoder in the same semantic space. To prevent trivial self-reconstruction without enforcing a hard zero diagonal, we introduce diagonal gating: a leave-one-item-out objective that blocks the self-copy shortcut only for the item being updated while retaining context from the rest of the user history. An alternating-style optimization trains the …

Ppg-Sport: A Dataset For Reliable Heart Rate Monitoring From Wrist Ppg Under Dynamic Sports Conditions, Changshuo Hu, Hung Manh Pham, Yiming Zhang, Guanru Yan, Xiao Ma, Yuezhong Wu, Thivya Kandappu, Archan Misra, Dong Ma

Research Collection School Of Computing and Information Systems

Photoplethysmography (PPG) has become a cornerstone of physiological sensing in wearable devices, enabling non-invasive monitoring of heart rate and related biomarkers. However, its reliability deteriorates sharply under dynamic, high-intensity, or non-periodic motions such as those in sports, where existing datasets fail to capture realistic wrist dynamics. To address this gap, we introduce PPG-Sport, the first large-scale dataset designed for heart rate monitoring from wrist-worn PPG under real sports conditions. The PPG-Sport dataset includes synchronized PPG, inertial measurement unit (IMU), and electrocardiography (ECG) recordings from both wrists of 30 participants across six representative activities: stationary, walking, running, badminton, table tennis, and …