Digital Commons Network^™

Unbounded Multi-Hop Proxy Re-Encryption With Hra Security: An Lwe-Based Optimization, Xiaohan Wan, Yang Wang, Haiyang Xue, Mingqiang Wang

Research Collection School Of Computing and Information Systems

Proxy re-encryption (PRE) schemes enable a semi-honest proxy to transform a ciphertext of one user i to another user j while preserving the privacy of the underlying message. Multi-hop PRE schemes allow a legal ciphertext to undergo multiple transformations, but for lattice-based multi-hop PREs, the number of transformations is typically bounded due to the increase of error terms. Recently, Zhao et al. (ESORICS 2024) introduced a lattice-based unbounded multi-hop (homomorphic) PRE scheme that supports an unbounded number of hops. Nevertheless, their scheme only achieves the selective CPA security. In contrast, Fuchsbauer et al. (PKC 2019) proposed a generic framework for …

Action Dubber: Timing Audible Actions Via Inflectional Flow, Wenlong Wan, Weiying Zheng, Tianyi Xiang, Guiqing Li, Shengfeng He

Research Collection School Of Computing and Information Systems

We introduce the task of Audible Action Temporal Localization, which aims to identify the spatiotemporal coordinates of audible movements. Unlike conventional tasks such as action recognition and temporal action localization, which broadly analyze video content, our task focuses on the distinct kinematic dynamics of audible actions. It is based on the premise that key actions are driven by inflectional movements; for example, collisions that produce sound often involve abrupt changes in motion. To capture this, we propose T A2Net, a novel architecture that estimates inflectional flow using the second derivative of motion to determine collision timings without relying on audio …

Leakage-Resilient Easily Deployable And Efficiently Searchable Encryption (Edese), Jiaming Yuan, Yingjiu Li, Jun Li, Daoyuan Wu, Jianting Ning, Yangguang Tian, Robert H. Deng

Research Collection School Of Computing and Information Systems

Easily Deployable and Efficiently Searchable Encryption (EDESE) is a cryptographic primitive designed for practical searchable applications, offering efficient search and easy deployment. However, it remains vulnerable to Leakage-Abuse attacks, allowing adversaries to exploit keyword-matching processes to extract sensitive information. To address these vulnerabilities, we introduce Leakage-Resilient EDESE (LR-EDESE) with k-indistinguishability and controlled leakage functions. We then propose Volume Leakage-Resilient EDESE (VLR-EDESE), a new scheme to protect against both query and document volume leakage. Our experimental results demonstrate that at k = 5000 (maximum security setting), VLR-EDESE incurs an overhead of 63× compared to the baseline EDESE without leakage protection, outperforming …

Surrogate Learning In Meta-Black-Box Optimization: A Preliminary Study, Zeyuan Ma, Zhiyang Huang, Jiacheng Chen, Zhiguang Cao, Yue-Jiao Gong

Research Collection School Of Computing and Information Systems

Recent Meta-Black-Box Optimization (MetaBBO) approaches have shown possibility of enhancing the optimization performance through learning meta-level policies to dynamically configure low-level optimizers. However, existing MetaBBO approaches potentially consume massive function evaluations to train their meta-level policies. Inspired by the recent trend of using surrogate models for cost-friendly evaluation of expensive optimization problems, in this paper, we propose a novel MetaBBO framework which combines surrogate learning process and reinforcement learning-aided Differential Evolution algorithm, namely Surr-RLDE, to address the intensive function evaluation in MetaBBO. Surr-RLDE comprises two learning stages: surrogate learning and policy learning. In surrogate learning, we train a Kolmogorov-Arnold Networks …

Ts-Diff: Two-Stage Diffusion Model For Low-Light Raw Image Enhancement, Yi Li, Zhiyuan Zhang, Jiangnan Xia, Jianghan Cheng, Qilong Wu, Junwei Li

Research Collection School Of Computing and Information Systems

This paper presents a novel Two-Stage Diffusion Model (TS-Diff) for enhancing extremely low-light RAW images. In the pre-training stage, TS-Diff synthesizes noisy images by constructing multiple virtual cameras based on a noise space. Camera Feature Integration (CFI) modules are then designed to enable the model to learn generalizable features across diverse virtual cameras. During the aligning stage, CFIs are averaged to create a target-specific CFIT, which is fine-tuned using a small amount of real RAW data to adapt to the noise characteristics of specific cameras. A structural reparameterization technique further simplifies CFIT for efficient deployment. To address color shifts during …

Sparse-To-Dense: A Free Lunch For Lossless Acceleration Of Video Understanding In Llms, Xuan Zhang, Cunxiao Du, Sicheng Yu, Jiawei Wu, Fengzhuo Zhang, Wei Gao, Qian Liu

Research Collection School Of Computing and Information Systems

Due to the auto-regressive nature of current video large language models (Video-LLMs), the inference latency increases as the input sequence length grows, posing challenges for the efficient processing of video sequences that are usually very long. We observe that during decoding, the attention scores of most tokens in Video-LLMs tend to be sparse and concentrated, with only certain tokens requiring comprehensive full attention. Based on this insight, we introduce Sparse-to-Dense (StD), a novel decoding strategy that integrates two distinct modules: one leveraging sparse top-K attention and the other employing dense full attention. These modules collaborate to accelerate Video-LLMs without loss. …

Rustmap: Towards Project-Scale C-To-Rust Migration Via Program Analysis And Llm, Xuemeng Cai, Jiakun Liu, Xiping Huang, Yijun Yu, Haitao Wu, Chunmiao Li, Bo Wang, Imam Nur Bani Yusuf, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Migrating existing C programs into Rust is increasingly desired, as Rust offers superior memory safety while maintaining C’s high performance. Existing automated translation tools, such as C2Rust, may rely too much on syntactic, template-based translation and generate unsafe Rust code that is hard for human developers to read, maintain, or even compile. More semantic-aware translation that produces safer, idiomatic, and runnable Rust code is much needed. This paper introduces a novel dependency-guided and large language model (LLM)-based C-to-Rust translation approach, RustMap, based on three key ideas: (1) Utilize LLM’s capabilities to produce idiomatic Rust code from given small pieces of …

Quantum Technologies In Decentralisation, Paul Robert Griffin, Rudy Raymond, Tsuyoshi Idé

Research Collection School Of Computing and Information Systems

Quantum technologies, rooted in the manipulation of quantum information, are revolutionizing computing and networking domains. Their impact on blockchains and decentralized systems is twofold. While much attention has been given to the potential of quantum computing to attack blockchains, these advanced technologies also offer avenues for strengthening and optimizing them. This chapter delves into the intricacies of quantum technologies, from the foundational concepts of qubits, quantum gates, and quantum networks to their implications for blockchains. We explore both the vulnerabilities of blockchains in a quantum-dominant era and the promising solutions quantum technologies provide, culminating in a use case examining their …

The Fiscal Deficit And National Debt: Can We Get It Right Once And For All?, Jesus Felipe, Mariel Monica Sauler

Angelo King Institute for Economic and Business Studies (AKI)

No abstract provided.

Atypical Beta Oscillatory Dynamics Are Related To Poor Procedural Learning In Children With Developmental Coordination Disorder, Jarrad A.G. Lum, Kaila M. Hamilton, Li Ann Leow, Welber Marinovic, Ian Fuelscher, Pamela Barhoun, Talitha C. Ford, Aron T. Hill, Samaneh Nahravani, Melissa Kirkovski, Peter G. Enticott, Christian Hyde

Research outputs 2022 to 2026

Procedural learning difficulties are commonly reported in children with developmental coordination disorder (DCD), yet the neural basis of this impairment remains unclear. This study addressed this gap by examining the correlation between cortical oscillatory activity and procedural learning of a sequence of finger movements in children with and without DCD. Participants were 19 children with DCD and 38 typically developing (TD) children, with a mean age of 10 years and 3 months. Children completed the Serial Reaction Time task, a standard measure of procedural learning, during which they unintentionally learned a sequence of finger movements. Electroencephalography (EEG) was continuously recorded …

Pharmacological Profiling Of Major Depressive Disorder-Related Multimorbidity Clusters, Tamas Nagy, Xenia Gonda, Andras Gezsi, Nora Eszlari, Gabor Hullam, Rubèn González-Colom, Hannu Mäkinen, Hannu Mäkinen, Mikko Kuokkanen

School of Medicine Publications

We previously identified seven distinct multimorbidity clusters associated with major depressive disorder through a comprehensive analysis of 1.2 million individuals of multiple cohorts. These clusters, characterized by unique clinical, genetic, and psychiatric and somatic illness risk profiles, implicate divergent treatment pathways and disease management strategies. This study aims to deepen the understanding of these clusters by analyzing drug prescriptions, evaluating the effectiveness of antidepressant treatment strategies, and identifying potential markers for personalized medicine. Utilizing drug prescription data in the format of ATC codes, we performed epidemiological assessments, including multimorbidity (number of diseases), polypharmacy (number of chemical substances), and …

Retraction: A Database Of Teleseismic Shear-Wave Splitting Measurements For The Ordos Block And Adjacent Areas(Seismological Research Letters (2022), 93, 5, (2731–2739), 10.1785/0220210310), Lin Liu, Stephen S. Gao, Kelly H. Liu, Tu Xue, Yan Jia, Sanzhong Li

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

An earlier version of this article (Liu et al., 2022) included private data from the Himalayan-III program which should not have been made public. The authors acknowledge and regret their negligence during the selection of the measurements. The impacted data represent only 2.7% of the total data published in this article, and after review, the authors and the editors agree that this unintentional error has no bearing on the work's scientific conclusions. Therefore, we are retracting the impacted data and have made corrections to remove any Himalayan-III program data from the article's text, figures, and supplemental tables.

The Potential And Perils Of Financializing Climate Risk Governance: Insights For Urban Policymakers, Emma Colven, Madison Condon, Kelly Hereid, Savannah Cox

Faculty Scholarship

In this roundtable discussion, Savannah Cox speaks with three experts about the financialization of climate risk governance: Kelly Hereid, a climate scientist at Liberty Mutual, Madison Condon, an associate professor at Boston University School of Law, and Emma Colven, a lecturer in risk, environment, and society at King’s College London. In this conversation that ranges from Miami to Jakarta, Savannah, Kelly, Madison, and Emma discuss the legal, political, and technical challenges relating to financialized climate risk governance: on one hand, the rise of insurance companies and rating agencies as de facto “risk assessors” and, on the other hand, the proliferation …

Civilian Enforcers, Karen Pita Loor

Faculty Scholarship

This Article analyzes the largely unexplored phenomenon of militant civilians engaged in efforts to police and silence activism that challenges entrenched American power systems and economic distributions placing whites atop the social hierarchy in the United States. I argue that this civilian enforcement is an unregulated vessel for state-sponsored violence meant to silence the contestation of the existing racial hierarchy. While scholars, myself included, have written about the many ways police confront and silence racial justice activists on the streets at least since the beginning of the Black Lives Matter (BLM) movement, the role law enforcement plays in silencing racial …

"What Shall Be Orthodox" In Polarized Times: Overview And Response To Commentators, Linda C. Mcclain, James E. Fleming

Faculty Scholarship

“If there is any fixed star in our constitutional constellation, it is that no official, high or petty, can prescribe what shall be orthodox in politics, nationalism, religion, or other matters of opinion or force citizens to confess by word or act their faith therein.” Justice Robert Jackson wrote this celebrated passage in his majority opinion in West Virginia State Board of Education v. Barnette (1943), which protected the First Amendment right of Jehovah’s Witness children not to participate in a compulsory flag salute in public schools. In recent years, protests against imposed orthodoxy—usually invoking Barnette—have occurred in …

A Historical Case For A Robust But Non-Remedial Seventh Amendment, Jed Handelsman Shugerman

Faculty Scholarship

In Jarkesy, the Supreme Court rightly held that the Seventh Amendment required a jury trial for a case fundamentally similar to common law fraud, and it rightly limited the scope of the “public rights” exception to the Seventh Amendment. Grounded in historical and originalist methods, this essay makes four suggestions after Jarkesy:

1. Following Jarkesy, the judiciary should continue a more robust enforcement of the Seventh Amendment right to a jury trial. The courts should eliminate the “public rights” exception to the Seventh Amendment, which does not appear to have an original link to the Seventh Amendment. The …

Dark Patterns As Disloyal Design, Johanna Gunawan, Woodrow Hartzog, Neil Richards, David Choffnes, Christo Wilson

Faculty Scholarship

Lawmakers have started to regulate “dark patterns,” understood to be design practices meant to influence technology users’ decisions through manipulative or deceptive means. Most agree that dark patterns are undesirable, but open questions remain as to which design choices should be subjected to scrutiny, much less the best way to regulate them.

In this Article, we propose adapting the concept of dark patterns to better fit legal frameworks. Critics allege that the legal conceptualizations of dark patterns are overbroad, impractical, and counterproductive. We argue that law and policy conceptualizations of dark patterns suffer from three deficiencies: First, dark patterns lack …

Ai-Based Classification Of Pediatric Breath Sounds: Toward A Tool For Early Respiratory Screening, Liu Lichuan, Wei Li, Elizabeth Moxley

Faculty Articles, Papers, and Other Scholarship

Context: Respiratory morbidity is a leading cause of children’s consultations with general practitioners. Auscultation, the act of listening to breath sounds, is a crucial diagnostic method for respiratory system diseases. Problem: Parents and caregivers often lack the necessary knowledge and experience to identify subtle differences in children’s breath sounds. Furthermore, obtaining reliable feedback from young children about their physical condition is challenging. Methods: The use of a human–artificial intelligence (AI) tool is an essential component for screening and monitoring young children’s respiratory diseases. Using clinical data to design and validate the proposed approaches, we propose novel methods for recognizing and …

Predicting & Analyzing University Success: Machine Learning Approaches To Predict Performance From Socioeconomic And Educational Data, Ali Alrais

Theses

Accurately predicting learner performance is a significant challenge in education since diverse and interrelated factors contribute to academic success. High school grades and standardized test scores remain the primary indicators used for university admissions. However, such approaches fail to capture the complexities surrounding student learning. For instance, various cognitive, cultural, socioeconomic, and environmental influences shape academic outcomes. Educators need to adopt more comprehensive predictive models that consider in-depth learner differences. Reliable academic performance prediction can help schools optimize admissions decisions, allocate resources effectively, and implement targeted interventions to support at-risk students. This study adopted a quantitative primary research approach with …

Investigating Spectral Rendering Techniques To Improve Colour Matching In Virtual Production, Vlad Simion

Theses

As rendering engines become increasingly important in film and television, with their use in virtual production (VP) to display rendered imagery, some underlying issues become more apparent. This thesis aims to investigate how we can improve asset color matching of VP elements with real-life objects found on sets. Experiments were conducted in which objects were exposed to various types of lighting setups, and digital twins were rendered using traditional computer graphics techniques. The renderings occurred in both classic RGB spaces and the spectral domain. Additionally, data reduction techniques were used for the spectral renderings to determine if any of them …

Identifying Underspecifications In Security Requirements Using A Formal Reasoning Approach, Viktoria Koscinski

Theses

Within requirements engineering, software requirements specifications tend to prioritize functional needs, potentially failing to capture critical security aspects and adequate security requirements. Security requirements engineering is a manual and error-prone activity often neglected due to the knowledge gap between cybersecurity professionals and software requirements engineers. Consequently, security requirements are especially prone to being underspecified, a condition where they lack a complete set of feature-values and are thus open to multiple interpretations. Underspecified security requirements can lead to incorrect assumptions and missing security properties, often remaining undiscovered until system deployment, thereby leaving the system vulnerable to exploitation. Furthermore, even individually well-written …

Online And Offline Multi-Variate Time Series Forecasting With Neuroevolution Based Neural Architecture Search, Zimeng Lyu

Theses

Time series forecasting plays a crucial role in various fields, ranging from financial markets and predictive maintenance in industrial settings to healthcare analytics. Traditionally, statistical approaches were employed primarily for univariate forecasting tasks, but modern applications often require robust solutions capable of handling complex, multivariate, noisy, and non-stationary data. Current state-of-the-art solutions predominantly utilize transformer-based models, which demand significant computational resources, limiting their practicality, especially in resource-constrained environments. This dissertation introduces novel and efficient approaches to multivariate time series forecasting, leveraging NeuroEvolution-based Neural Architecture Search (NAS) methodologies. Specifically, two robust algorithms---Evolutionary eXploration of Augmenting Memory Models (EXAMM) for offline forecasting …

Cutting Through Stigma: Suggested Best Practices For Aharm Reduction Approach To Nonsuicidal Self-Injury, Lindsay Lundeen, Erin Kern Popejoy

Counseling, Leadership, and Research Methods Faculty Publications and Presentations

For many counselors, both topics of nonsuicidal self-injury (NSSI) and harm reduction practices can feel intimidating and unclear. Yet, depending on the client, discussion of complete and immediate cessation from NSSI can feel impossible and isolating. This article combines harm reduction principles, a concept initially developed for addiction treatment, with select existing recommendations for NSSI treatment to offer a clinician's guide to best practices for harm reduction implementation with clients engaging in NSSI. By meeting clients where they are and offering a supportive space to brainstorm nontraditional treatment options, counselors can maintain the core principles of the American Counseling Association's …

Explainable Use Of Foundation Models For Job Hiring, Vishnu S. Pendyala, Neha Bais Thakur, Radhika Agarwal

Faculty Research, Scholarly, and Creative Activity

Automating candidate shortlisting is a non-trivial task that stands to benefit substantially from advances in artificial intelligence. We evaluate a suite of foundation models such as Llama 2, Llama 3, Mixtral, Gemma-2b, Gemma-7b, Phi-3 Small, Phi-3 Mini, Zephyr, and Mistral-7b for their ability to predict hiring outcomes in both zero-shot and few-shot settings. Using only features extracted from applicants’ submissions, these models, on average, achieved an AUC above 0.5 in zero-shot settings. Providing a few examples similar to the job applicants based on a nearest neighbor search improved the prediction rate marginally, indicating that the models perform competently even without …

A Simple Model Of Spiral Galaxies From Geometric Optics, Bogdan Szafraniec, James N. Blake

Faculty Research, Scholarly, and Creative Activity

We propose a simple model of spiral galaxies based on the interference of gravitational waves. The interference is deduced from geometric optics analysis of the refractive index profiles that mimic the behavior of gravitational potentials −1/r and r². We analyze the refractive index profiles, n(r)² = a + b/r and n(r)² = a + br², because they are realistically shaped and yield closed form solutions. The two profiles yield similar physical results, showing that the physical interpretation is not dependent on the exact details of the profile. The first profile yields trajectories that can …

The Settlement Privacy-Transparency Matrix: Moving Beyond The Dichotomous Mindset In The Settlement Debate, Alyson Carrel, Peter K. Chan

Journal of Dispute Resolution

The philosopher Arthur Schopenhauer once wrote, “The first forty years of life give us the text; the next thirty supply the commentary on it.” Forty years after Owen Fiss’s seminal article “Against Settlement,” it is time to reimagine how we approach the settlement debate beyond traditional dichotomies. Just as Schopenhauer recognized that time and experience allow us to better understand our past, forty years of grappling with the settlement debate have given us the perspective to see its limitations, and now with emerging technologies, new possibilities. The ‘text’ of the debate—its dichotomous framing and distributive solutions—has shaped four decades of …

Psychology And Dispute Resolution: Looking Forward, Jennifer K. Robbennolt

Journal of Dispute Resolution

There is a long and deep history of interconnection between dispute resolution and psychology. Concepts like procedural justice permeate the literature. Psychologists have investigated and provided data about phenomena such as the fixed pie bias, impasse aversion, and reactive devaluation. Research drawing on the psychology of heuristics and biases has been influential, particularly in work on settlement decision making. Studies in this tradition have explored how framing, anchoring, anticipated regret, and different ways of considering options can influence the decisions made by disputants. Psychologists have explored the role of apologies in dispute resolution, the role of emotion in negotiation, and …

Surface Keratin 1, A Tumor-Selective Peptide Target In Human Triple-Negative Breast Cancer, Shih-Jing Yao, Farideh Amirrad, Elmira Ziaei, Azam Saghaeidehkordi, Moom R. Roosan, Kiumars Shamloo, Ajay Sharma, Rachita K. Sumbria, Surya M. Nauli, Christopher G. Bunick, Kamaljit Kaur

Pharmacy Faculty Articles and Research

Targeting drugs to cancer cells via overexpressed cell-surface receptors has emerged as an effective therapeutic strategy for several cancers. However, identifying cell-surface receptors that allow selective uptake of targeting ligands by cancer cells—while sparing normal cells—remains a challenge, especially for triple-negative breast cancer (TNBC), which lacks a well-defined receptor for targeted delivery. In this study, immunohistochemical (IHC) analysis revealed that human TNBC patient tissues have significantly higher levels of keratin 1 (K1) compared to normal breast tissues. Among TNBC tissues, grade 3 tumors showed significantly higher (threefold) K1 expression compared to grade 2 tumors. We analyzed human TNBC and normal …

Reduction Of Neuronal Activity Mediated By Blood-Vessel Regression In The Adult Brain, Xiaofei Gao, Xing-Jun Chen, Meng Ye, Jun-Liszt Li, Nannan Lu, Di Yao, Bo Ci, Fei Chen, Lijun Zheng, Yating Yi, Shiwen Zhang, Zhanying Bi, Xinwei Gao, Yuanlei Yue, Tingbo Li, Jiafu Lin, Ying-Chao Shi, Kaibin Shi, Nicholas E Propson, Yubin Huang, Katherine Poinsatte, Zhaohuan Zhang, Dale B Bosco, Shi-Bing Yang, Ralf H Adams, Volkhard Lindner, Fen Huang, Long-Jun Wu, Hui Zheng, Simon Hippenmeyer, Ann M Stowe, Bo Peng, Marta Margeta, Qingchun Guo, Xiaoqun Wang, Qiang Liu, Jakob Körbelin, Martin Trepel, Hui Lu, Guoen Cai, Bo O Zhou, Bo Shen, Ying-Mei Lu, Wenzhi Sun, Jie-Min Jia, Feng Han, Hu Zhao, Robert M Bachoo, Woo-Ping Ge

Center on Aging Staff Publications

The brain vasculature supplies neurons with glucose and oxygen, but little is known about how vascular plasticity contributes to brain function. Using longitudinal in vivo imaging, we report that a substantial proportion of blood vessels in the adult mouse brain sporadically occlude and regress. Their regression proceeds through sequential stages of blood-flow occlusion, endothelial cell collapse, relocation or loss of pericytes, and retraction of glial endfeet. Regressing vessels are found to be widespread in mouse, monkey and human brains. We further reveal that blood vessel regression cause a reduction of neuronal activity due to a dysfunction in mitochondrial metabolism and …

Definition And Classification Of Dystonia, Alberto Albanese, Kailash P Bhatia, Victor S C Fung, Mark Hallett, Joseph Jankovic, Christine Klein, Joachim K Krauss, Anthony E Lang, Jonathan W Mink, Sanjay Pandey, Jan K Teller, Marina A J Tijssen, Marie Vidailhet, H A Jinnah

Faculty, Staff and Students Publications

Dystonia is a movement disorder with varied clinical features and diverse etiologies. Here we present a revision of the 2013 consensus definition and classification of dystonia in light of subsequent publications and experience with its application during the last decade. A panel of movement disorder specialists with expertise in dystonia reviewed the original document and proposed some revision. There was broad consensus to retain the definition of dystonia with only minor clarifications to the wording. Dystonia is defined as a movement disorder characterized by sustained or intermittent abnormal movements, postures, or both. Dystonic movements and postures are typically patterned and …