Digital Commons Network^™

Teaching Diffusion Models To Ground Alpha Matte, Tianyi Xiang, Weiying Zheng, Yutao Jiang, Tingrui Shen, Hewei Yu, Yangyang Xu, Shengfeng He

Research Collection School Of Computing and Information Systems

The power of visual language models is showcased in visual understanding tasks, where language-guided models achieve impressive flexibility and precision. In this paper, we ex tend this capability to the challenging domain of image matting by framing it as a soft grounding problem, enabling a single diffusion model to handle diverse objects, textures, and transparencies, all directed by descriptive text prompts. Our method teaches the diffusion model to ground alpha mattes by guiding it through a process of instance-level localization and transparency estimation. First, we introduce an intermediate objective that trains the model to accurately localize semantic components of the …

Visual-Enhanced Multimodal Framework For Flexible Job Shop Scheduling Problem, Peng Zhao, Zhiguang Cao, Di Wang, Wen Song, Wei Pang, You Zhou, Yuan Jiang

Research Collection School Of Computing and Information Systems

Multimodal models leverage complementary information across modalities to enrich feature representations. While visual information shows potential in representing structure for some combinatorial optimization problems (COPs), its application to complex scheduling like the Flexible Job Shop Scheduling Problem (FJSP) remains underexplored. Current learning-based FJSP solvers predominantly rely on handcrafted state features. This dependence can lead to inconsistencies and may not fully capture the problem's intricate dynamics. Crucially, these methods overlook visual modalities. Visual representations offer a distinct advantage by inherently capturing the global topological structure and complex resource interactions within the FJSP state. Unlike localized handcrafted features, this holistic, structural view …

A Comprehensive Review Of Financial Knowledge Graphs, Jeyaraman Brindha Priyadarshini, Bing Tian Dai, Yuan Fang

Research Collection School Of Computing and Information Systems

Knowledge Graphs (KGs) are increasingly used in finance to manage complex, interconnected data and support advanced analytics. This survey provides an overview of how KGs are applied across various financial areas, such as fraud detection, credit risk assessment, anti-money laundering, and regulatory compliance. We examine key techniques for building and using KGs in finance, including graph construction, embedding methods, and machine learning models. The survey also discusses challenges specific to finance, like handling private data, ensuring interpretability, and managing real-time data. Additionally, we explore the emerging combination of KGs with large language models and generative AI, which offers new possibilities …

Polymind: Parallel Visual Diagramming With Large Language Models To Support Prewriting Through Microtasks, Qian Wan, Jiannan Li, Huanchen Wang, Zhicong Lu

Research Collection School Of Computing and Information Systems

Prewriting is the process of generating and organising ideas before a first draft. It consists of a combination of informal, iterative, and semi-structured strategies such as visual diagramming, which poses a challenge for collaborating with large language models (LLMs) in a turn-taking conversational manner. We present Polymind, a visual diagramming tool that leverages multiple LLM-powered agents to support prewriting. The system features a parallel collaboration workflow in place of the turn-taking conversational interactions. It defines multiple ''microtasks'' to simulate group collaboration scenarios such as collaborative writing and group brainstorming. Instead of repetitively prompting a chatbot for various purposes, Polymind enables …

Information Provision And Search Frictions: Evidence From The Taxi Industry In Singapore, Sumit Agarwal, Shih-Fen Cheng, Jussi Keppo, Long Wang, Yang Yang

Research Collection School Of Computing and Information Systems

Search frictions and misallocation are common in decentralized transportation markets. Using novel trip-level data of taxis in Singapore, this paper examines the impactof real-time demand information at airport terminals on search frictions. The information reduces taxi supply misallocation, increasing deadheading speed by 16.3% and decreasing deadheading time by 10.77%, benefiting both passengers and drivers. It raises daily earnings by $3.70 USD and adds 6.2 minutes of operational time per airport-trip taxi. Spatial spillovers are primarily observed among drivers in adjacentdistricts. Taxis from the Budget Terminal and drivers with fewer prior airport pickups benefit more from this information.

Cross-Subject Mind Decoding From Inaccurate Representations, Yangyang Xu, Bangzhen Liu, Wenqi Shao, Yong Du, Shengfeng He, Tingting Zhu

Research Collection School Of Computing and Information Systems

Decoding stimulus images from fMRI signals has advanced with pre-trained generative models. However, existing methods struggle with cross-subject mappings due to cognitive variability and subject-specific differences. This challenge arises from sequential errors, where unidirectional mappings generate partially inaccurate representations that, when fed into diffusion models, accumulate errors and degrade reconstruction fidelity. To address this, we propose the Bidirectional Autoencoder Intertwining framework for accurate decoded representation prediction. Our approach unifies multiple subjects through a Subject Bias Modulation Module while leveraging bidirectional mapping to better capture data distributions for precise representation prediction. To further enhance fidelity when decoding representations into stimulus images, …

Lsfdnet: A Single-Stage Fusion And Detection Network For Ships Using Swir And Lwir, Yanyin Guo, Runxuan An, Junwei Li, Zhiyuan Zhang

Research Collection School Of Computing and Information Systems

Traditional ship detection methods primarily rely on single-modal approaches, such as visible or infrared images, which limit their application in complex scenarios involving varying lighting conditions and heavy fog. To address this issue, we explore the advantages of short-wave infrared (SWIR) and long-wave infrared (LWIR) in ship detection and propose a novel single-stage image fusion detection algorithm called LSFDNet. This algorithm leverages feature interaction between the image fusion and object detection subtask networks, achieving remarkable detection performance and generating visually impressive fused images. To further improve the saliency of objects in the fused images and improve the performance of the …

Parameter-Efficient Variational Autoencoder For Multimodal Multi-Interest Recommendation, Nhu Thuat Tran, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

Learning user preferences in recommendation systems is enriched by multimodal features, such as textual and visual content, and amplified by multi-interest modeling with Variational AutoEncoders (VAEs). However, prior efforts are limited by single modality focus and cumbersome, parameter-heavy architecture designs. To address these limitations, we introduce an innovative solution that blends the semantic richness of multimodal data with the representational power of multi-representation VAEs. Drawing inspiration from Mixture of Experts (MoE), we cast each VAE as an expert tailored to a specific modality, then fuse them via a novel parameter-merging function into a lean, unified model. This approach efficiently captures …

Search Trajectory Network-Enhanced Multi-Objective Dynamic Algorithm Configuration, Robbert Reijnen, Zaharah Bukhsh, Hoong Chuin Lau, Yaoxin Wu, Yingqian Zhang

Research Collection School Of Computing and Information Systems

Deep reinforcement learning (DRL) has emerged as an effective technique for dynamic algorithm configuration, particularly in evolutionary computation, enabling adaptive parameter updates during algorithmic execution. DRL-based methods have shown broad applicability across different problem domains and are designed to configure algorithms without problem-specific information, making them highly transferable across problem variants and scalable to different problem sizes. This paper proposes a novel graph neural network-based approach that learns representations of Search Trajectory Networks (STNs) to track the convergence behavior of multiple objectives and dynamically reconfigures multiobjective evolutionary algorithms during execution. By capturing how solutions evolve and interact over time, the …

Website Owner Identification Through Multi-Level Contrastive Representation Learning, Cheng Tu, Yunshan Ma, Yang Li, Min Zhang, Miao Hu, Fan Shi, Xiang Wang

Research Collection School Of Computing and Information Systems

Website owner identification aims to recognize the organization or individual who owns a given website that is served on the web. It is a crucial step for cyberspace surveying and mapping, playing a significant role in cyberspace administration and governance. Existing widely employed solutions for website owner identification mainly fall into two paradigms: (1) querying the public information databases such as WHOIS, which store the Internet resource’s registered users or assignees; and (2) directly extracting the organization or individual name of the website owner from the webpage using the technique of named entity recognition. However, the former is less reliable …

Ivycross: A Privacy-Preserving And Concurrency Control Framework For Blockchain Interoperability, Ming Li, Jian Weng, Jia-Si Weng, Yi Li, Yongdong Wu, Dingcheng Li, Guowen Xu, Deng, Robert H.

Research Collection School Of Computing and Information Systems

Interoperability is a fundamental challenge for long-envisioned blockchain applications. A mainstream approach is using Trusted Execution Environment (TEE) to support interoperable off-chain execution. However, this incurs multiple TEE configured with non-trivial storage capabilities running on fragile concurrent processing environments, rendering current strategies based on TEE far from being practical. This paper aims to fill this gap and design a practical interoperability mechanism with simplified TEE as the underlying architecture. Specifically, we present IvyCross, a TEE-based framework that achieves low-cost, privacy-preserving, and race-free blockchain interoperability. IvyCross allows running arbitrary smart contracts across heterogeneous blockchains atop two distributed TEE-powered hosts. We design …

Information-Bottleneck Driven Binary Neural Network For Change Detection, Kaijie Yin, Zhiyuan Zhang, Shu Kong, Tian Gao, Cheng-Zhong Xu, Hui Kong

Research Collection School Of Computing and Information Systems

In this paper, we propose Binarized Change Detection (BiCD), the first binary neural network (BNN) designed specifically for change detection. Conventional network binarization approaches, which directly quantize both weights and activations in change detection models, severely limit the network's ability to represent input data and distinguish between changed and unchanged regions. This results in significantly lower detection accuracy compared to real-valued networks. To overcome these challenges, BiCD enhances both the representational power and feature separability of BNNs, improving detection performance. Specifically, we introduce an auxiliary objective based on the Information Bottleneck (IB) principle, guiding the encoder to retain essential input …

Auxiliary Prompt Tuning Of Vision‑Language Models For Few‑Shot Out‑Of‑Distribution Detection, Wenjun Miao, Guansong Pang, Zihan Wang, Jin Zheng, Xiao Bai

Research Collection School Of Computing and Information Systems

Recent advancements in CLIP-based out-of-distribution (OOD) detection have shown promising results via regularization on prompt tuning, leveraging background features extracted from a few in-distribution (ID) samples as proxies for OOD features.However, these methods suffer from an inherent limitation: a lack of diversity in the extracted OOD features from the few-shot ID data.To address this issue, we propose to leverage external datasets as auxiliary outlier data (i.e., pseudo OOD samples) to extract rich, diverse OOD features, with the features from not only background regions but also foreground object regions, thereby supporting more discriminative prompt tuning for OOD detection. We further introduce …

Contrastrepair: Enhancing Conversation-Based Automated Program Repair Via Contrastive Test Case Pairs, Jiaolong Kong, Xiaofei Xie, Mingfei Cheng, Shangqing Liu, Xiaoning Du, Qi Guo

Research Collection School Of Computing and Information Systems

Automated Program Repair (APR) aims to automatically generate patches for rectifying software bugs. Recentstrides in Large Language Models (LLM), such as ChatGPT, have yielded encouraging outcomes in APR,especially within the conversation-driven APR framework. Nevertheless, the efficacy of conversation-drivenAPR is contingent on the quality of the feedback information. In this article, we propose ContrastRepair, anovel conversation-based APR approach that augments conversation-driven APR by providing LLMs withcontrastive test pairs. A test pair consists of a failing test and a passing test, which offer contrastive feedback tothe LLM. Our key insight is to minimize the difference between the generated passing test and the …

Morphology-Aware Hrv Estimation From Wrist Ppg In Sedentary Scenarios, Changshuo Hu, Hung Manh Pham, Dong Ma

Research Collection School Of Computing and Information Systems

Photoplethysmography (PPG) is widely used in wearable devices for non-invasive heart rate variability (HRV) monitoring. While most prior work focuses on mitigating motion artifacts, recent studies highlight that even subtle contact pressure variations can distort waveform morphology and lead to inaccurate HRV estimates. In this work, we propose a morphology-aware deep learning framework that conditions HRV estimation on beat-level waveform types. Our model jointly encodes the raw PPG waveform and a sequence of pressure-induced morphology labels using parallel encoders, integrates them via cross-attention, and predicts normal-to-normal (NN) intervals and beat count to support downstream HRV computation. Evaluated on the public …

Impact Of Original Versus Reposted Social Endorsements On Content Consumption: The Moderating Role Of Endorsers’ Network Characteristics, Anqi Zhao, Qian Tang

Research Collection School Of Computing and Information Systems

Social endorsements broadcast endorsers’ positive attitudes toward content or products, especially to their social ties. Original endorsements created by endorsers can be propagated further as reposted endorsements. Both are important marketing tools to increase content consumption, yet their differences are unclear. This study compares the impacts of original and reposted endorsements on content consumption and their contingencies on the endorsers’ network characteristics. Using data on social endorsements of YouTube videos on Twitter, we find that original endorsements (i.e., original tweets) significantly boost content consumption, and the effect is positively moderated by the endorsers’ network size but not their tie strength. …

Through His Eyes: The Life Of American Pows In Germany And Ben Phelper’S Diary, Bianca Shah

Armstrong Undergraduate Journal of History

This paper aims to examine the treatment American prisoners of war experienced at the hands of their German captors during World War II. Ben Phelper, a US Airman who was taken captive by the Germans from 1943-1945, wrote a diary detailing his daily life while living in the stalags. This research uses Phelper’s diary to understand what life was like for Americans in German POW camps and compares Phelper’s experience to existing literature on how Germans treated their American POWs. This paper specifically focuses on four aspects of Phelper’s life in relation to the provisions of the Geneva Convention, the …

Qisas: The Incremental Formation Of Jihad Amidst The Islamic Mujahideen Across The Middle And Near East, Jenny N. Liang

Armstrong Undergraduate Journal of History

Since its inception in seventh-century Arabia, Islamic thought and the concept of jihad have been present among Islamic scholars. Nevertheless, despite a history of conflict with Western nations through religious wars in the Near and Middle East, the rapid transformation of Islamic extremism by means of global terrorism in the late twentieth- and early twenty-first century ultimately traces to the Soviet invasion of Afghanistan and the rise of the Mujahideen. Islamic yearning for retribution through strategic retaliation began after December 1979, when Soviet Red Army troops invaded Afghanistan. Following the resolution of World War II and the emergence of a …

Digital Leadership: Secondary Education Principals’ Perceptions And Change Competencies Toward Implementing Digital Citizenship Curricula, Waylon M. Randolph

Electronic Theses and Dissertations

Secondary education public schools are increasingly being confronted with student misuse of information and communication technologies (ICTs). Students are using these technologies to engage in disruptive and harmful behaviors like cyberbullying and sexting. As a result, some public school districts have responded by banning the use of ICTs in the classroom, while others have turned to teaching digital citizenship through a dedicated digital citizenship curriculum. However, effectively implementing such a curriculum remains a significant challenge. According to the literature, the best way to implement a digital citizenship curriculum is by fostering a positive school culture where stakeholders model and support …

Management Of Recurrent Metastasis Of Renal Cell Carcinoma To The Parotid Gland After Nephrectomy., Kathryn Collins, Emily Cushing, Alex Ellerhorst, Christopher Selinsky

Oncology Articles

Renal cell carcinoma accounts for 90% of malignant renal tumors, with common metastases to the lungs, bones, and brain. Head and neck metastases are uncommon, and the parotid gland is an exceedingly rare site (0.5%). Recurrent metastasis to bilateral parotid glands has been reported in the literature, but recurrent metastasis to the ipsilateral gland has not. This is a case about a 69-year-old female who presented to our clinic with the chief complaint of a slowly enlarging left neck mass. She had a history of clear cell renal cell carcinoma treated with nephrectomy 15 years prior. An MRI reviewed from …

Identification Of Surrogate Outcome Biomarkers In Lung Allograft Recipients With Bronchiolitis Obliterans: Implications For Randomized Controlled Trials, Derek E. Byers, Suresh Vedantham, Mary Clare Derfler, Paul Commean, Andrew Atkinson, Jeff Atkinson, Alexey Prokudin, John Mccarthy, George Despotis, Et Al.

2020-Current year OA Pubs

BACKGROUND: We developed a prospective, multicenter "registry" to evaluate the effect of extracorporeal photopheresis for lung transplant recipients who develop chronic lung allograft dysfunction (CLAD) with the bronchiolitis obliterans syndrome (BOS) phenotype (CLAD/BOS) and who are refractory to conventional standard-of-care therapy.

METHODS: Data from 258 lung transplant recipients enrolled in the Registry between April 2015 and April 2022 were included in this analysis. All recorded parameters (eg, demographics), including forced expiratory volume in 1 s (FEV

RESULTS: Mortality at 6 and 12 mo after CLAD/BOS diagnosis was 5% and 14%, whereas mortality at 6 and 12 mo after enrollment was …

Gut Complement System: A New Frontier In Microbiota-Host Communication And Intestinal Homeostasis, Xianbin Tian, Lan Zhang, Xinyang Qian, Yangqing Peng, Fengyixin Chen, Sarah Bengtson, Zhiqing Wang, Meng Wu

2020-Current year OA Pubs

The gut microbiota plays a crucial role in maintaining intestinal homeostasis and influencing various aspects of host physiology, including immune function. Recent advances have highlighted the emerging importance of the complement system, particularly the C3 protein, as a key player in microbiota-host interactions. Traditionally known for its role in innate immunity, the complement system is now recognized for its interactions with microbial communities within the gut, where it promotes immune tolerance and protects against enteric infections. This Review explores the gut complement system as a possibly novel frontier in microbiota-host communication and examines its role in shaping microbial diversity, modulating …

“If I Can Accept My Queerness, I Can Accept My Body As It Is”: Understanding Weight-Related Perspectives And Stigma From Sexual Minority Women, Lauren A. Fowler, Yilin Wang, Catherine Wall, Allyson Velkovich, Erin N. Harrop, Melissa M. Vázquez, Janis Mensah, Annessa Flentje, Emily S. Mann Ph.D.

Faculty Publications

Introduction:

Sociocultural norms that conflate thinness with health and morality contribute to widespread weight stigma, with well-documented consequences for physical and mental health. Sexual minority women (SMW), particularly those living in larger bodies, may be especially affected due to the intersection of heterosexism, sexism, and weight stigma across their lives.

Methods:

This qualitative study utilized life history-informed semi-structured interviews with 24 cisgender SMW, ages 22–46, to explore how they experience sociocultural messages about weight, body size, and health over time, and how these experiences intersect with other aspects of structural marginalization. Interviews were audio recorded and transcripts were coded using …

Rtn4ip1 Is Required For The Final Stages Of Mitochondrial Complex I Assembly And Coq Biosynthesis, Monika Oláhová, Rachel M Guerra, Jack J Collier, Juliana Heidler, Kyle Thompson, Chelsea R White, Paulina Castañeda-Tamez, Alfredo Cabrera-Orefice, Robert N Lightowlers, Zofia M A Chrzanowska-Lightowlers, Alexander Galkin, Ilka Wittig, David J Pagliarini, Robert W Taylor

2020-Current year OA Pubs

A biochemical deficiency of mitochondrial complex I (CI) underlies approximately 30% of cases of primary mitochondrial disease, yet the inventory of molecular machinery required for CI assembly remains incomplete. We previously characterised patients with isolated CI deficiency caused by segregating variants in RTN4IP1, a gene that encodes a mitochondrial NAD(P)H oxidoreductase. Here, we demonstrate that RTN4IP1 deficiency causes a CI assembly defect in both patient fibroblasts and knockout cells, and report that RTN4IP1 is a bona fide CI assembly factor. Complexome profiling revealed accumulation of unincorporated ND5-module and impaired N-module production. RTN4IP1 patient fibroblasts also exhibited defective coenzyme Q biosynthesis, …

Gender Trends In Professional Advancement Among Academic Pediatric Neurologists, Juliet K Knowles, Renée A Shellhaas, Et Al.

2020-Current year OA Pubs

No abstract provided.

Ibrutinib Added To Standard Conditioning And As Maintenance Therapy Following Autologous Hematopoietic Stem Cell Transplantation For Relapsed Or Refractory Activated-B-Cell Type Diffuse Large B-Cell Lymphoma: Primary Analysis Of The Us Intergroup Double-Blind Randomized Phase Iii Study Alliance A051301/Bmt-Ctn 1201, Charalambos Andreadis, Brad S Kahl, Nancy L Bartlett, Et Al.

2020-Current year OA Pubs

To improve outcomes in relapsed or refractory activated B-cell type Diffuse Large B-cell Lymphoma (ABC-DLBCL), we launched a randomized phase 3 trial evaluating 2-year progression free survival (2yPFS) with the addition of ibrutinib to autologous transplant. Patients received ibrutinib 560 mg or placebo with conditioning and for 12 additional cycles. Accrual was adversely affected by implementation of the ABC classifier in this setting and the changing treatment landscape of DLBCL. In all, 39 patients on ibrutinib and 38 on placebo were evaluable. 2yPFS was 57.6% on ibrutinib versus 40.8% on placebo (

Do Complex Psychometric Analyses Really Matter? Comparing Multiple Approaches Using Individual Participant Data From Antidepressant Trials, David Byrne, Frank Doyle, Susan Brannick, Robert M Carney, Pim Cuijpers, Alexandra L Dima, Kenneth E Freedland, Suzanne Guerin, David Hevey, Bishember Kathuria, Emma Wallace, Fiona Boland

2020-Current year OA Pubs

BACKGROUND: Psychometric methods are used to remove underperforming items and reduce error in existing measures, albeit different approaches can produce different results. This study aimed to determine the implications of applying different psychometric methods for clinical trial outcomes.

METHODS: Individual participant data from 15 antidepressant treatment trials from Vivli.org were analyzed. Baseline (pretreatment) and 8-week (range 4-12 weeks) outcome data from the Montgomery-Asberg Depression Rating Scale were subjected to best-practice factor analysis (FA), item response theory (IRT), and network analysis (NA) approaches. Trial outcomes for the original summative scores and psychometric-model scores were assessed using multilevel models. Percentage differences in …

Family Income And Polygenic Scores Are Independently But Not Interactively Associated With Cognitive Performance Among Youth Genetically Similar To European Reference Populations, S E Paul, N M Elsayed, S M C Colbert, R Bogdan, A S Hatoum, D M Barch

2020-Current year OA Pubs

Cognitive abilities are heritable and influenced by socioeconomic status (SES). It is critical to understand the association between SES and cognition beyond genetic propensity to inform potential benefits of SES-based interventions and to determine if such associations vary across (i) cognitive domains, (ii) facets of SES, and/or (iii) genetic propensity for different aspects of cognition. We examined the contributions of neighborhood socioeconomic advantage, family income, and polygenic scores (PGS) for domains of cognition (i.e., general cognitive ability, executive function, learning and memory, fluid reasoning) in a sample of children (ages 9-10;

Remorse For Discrimination: The Role Of Group Dominance In Judging Hate Crimes Against Subordinate Group Members, Andrés Gvirtz, Patrick F. Kotzur, Andrew Stewart, Felicia Pratto

Psychology

Power, especially in the court system, is a potent determinant of intergroup relationships. Blind justice being only an ideal, public opinion can influence whether harm to low power groups is considered criminal and should be prosecuted. Our experiments investigated the impact of social dominance orientation (SDO) on the perceived appropriateness of punishment for harm to subordinate group members by dominant group members. Further, we examined the moderating role of a remorseful apology. We argue that perpetrators who do not show remorse towards their less powerful victim might be judged less harshly by those scoring high in SDO. Apologizing for the …

Data-Driven Optimization And Parameter Estimation For A Metric Graph Epidemic Model With Applications To Covid-19 Spread In Poland: A Real-World Example Of Optimization For A Challenging Rosenbrock-Type Objective Function, Hannah Kravitz, Christina Duron, Brittani Nieves, Moysey Brio

Mathematics and Statistics Faculty Publications and Presentations

In this paper, we apply data-driven optimization to estimate key parameters in a metric graph-based epidemiological model, with the aim of analyzing the effect of road networks on the geographic spread of epidemics. As a case study, we fit our model to data from the COVID-19 pandemic in Poland during 2021. Our dataset integrates county-level daily case reports, national census information, and traffic flow studies. This framework allows us to examine the relative contribution of specific travel routes over time and infer unobserved transmission patterns in the presence of incomplete or unreliable case reporting. The optimization problem that arises from …