Digital Commons Network^™

Synchronizing Work And Teaching Practices With The Spatial Dna Of Distributed Work And Learning, Manju Aishwarya Adikesavan

Dissertations, Theses, and Capstone Projects

Phygitality, the seamless and synergistic integration of physical and digital realms, is an indispensable and irrevocable part of contemporary office-based work. Phygitality facilitates spatially and temporally distributed or multi-local working where employees work from diverse locations such as their home, office, and third places at any time of day or night. It also makes nonterritorial working at temporary workspaces accessed on a session-by-session basis possible.

This dissertation examines how phygital, multi-local, and nonterritorial working reshape individual and group work behaviors, organizational spatial practices, work-centric settings, non-work-centric settings, neighborhoods, cities, and regions. The Spatial DNA of Distributed Work encapsulates a conceptual …

Vertex-Based Analysis Of Cerebral Blood Flow And Fractional Amplitude Of Low-Frequency Fluctuations (Cbf-Falff) Coupling In Moderate-To-Severe Traumatic Brain Injury During The First Year Post-Injury, Vaidehi Hemkumar Patel

Dissertations, Theses, and Capstone Projects

Traumatic brain injury (TBI) is known to involve damage in the neurovascular unit. TBI may disrupt the brain’s neurovascular coupling–the relationship between cerebral blood flow and neural activity–that can lead to cognitive and functional impairments. This study attempted to non-invasively investigate neurovascular coupling in patients with moderate to severe TBI (msTBI) during the first year post-injury using a combined metric of cerebral blood flow (CBF) and fractional amplitude of low-frequency fluctuations (fALFF), a proxy for spontaneous neural activity. Using arterial spin labeling (ASL) and functional MRI sequences, CBF and fALFF were measured in 29 msTBI patients 3-, 6- and 12-months …

On The Ambiguity Of Wh-Expressions In Thai, Naparat Meechanyakul

Dissertations, Theses, and Capstone Projects

This dissertation deals with an ambiguity problem of wh-indeterminates in Thai. Thai wh-phrases are indeterminates in that their interpretations depend on licensing conditions and structural environments. In this dissertation, observed ambiguous interpretations of object wh-arguments in Thai are described and analyzed through the lens of a phase-based approach under the Minimalist Program. The ambiguity problem concerns the fact that ʔàraj ‘what’ and khraj ‘who’ receive two possible interpretations, namely indefinite/NPI and interrogative, when they appear as an internal argument of serialized verb phrases and under c-commanding negation. Other wh-phrases in the language, namely the locative wh …

Where The Landscape Inspires The Lines: Python-Based Workbooks And Digital Tools For Reading Yoshino Ki, Miaoling Xue

Dissertations, Theses, and Capstone Projects

Where the Landscape Inspires the Lines (https://yoshinoki.info/) explores the intersection of premodern Japanese literature and digital humanities (DH) through an innovative online platform for reading, annotating, and coding. Centered on Yoshino ki 吉野記 (A Record of Yoshino), a seventeenth-century Japanese poetic travelogue authored by the poet and courtier Asukai Masaaki 飛鳥井雅章 (1611–1679), this project offers an interactive and immersive experience designed to meet the academic and research needs of a diverse group of scholars and students while advocating for a multilingual approach that challenges anglophone-centric biases often found in DH. To ensure consistency, the project uses Yoshino ki as a …

Does Treatment Setting In Ati Matter? An Examination Of Completion Rates And The Role Of Violent Charges Among Individuals With Co-Occurring Disorders, George J. Anderson

Dissertations, Theses, and Capstone Projects

Despite the proliferation of alternatives to incarceration (ATI) for individuals with co-occurring disorders in recent decades, little is known about comparative styles of treatment used in this context. The following study uses data from a case management service in a large urban city (n=273) where several types of treatment are utilized in the ATI landscape. Specifically, this study compares ATI completion rates and time to completion or failure for several styles of treatment: clinic-based outpatient, residential, assertive community treatment (ACT) and personalized recovery-oriented services (PROS) programs. Results of a logistic regression indicate that individuals initially referred to residential treatment had …

Inherited Wounds: Generational Trauma In Postcolonial Film And Narrative Fiction Of The Global South, Sabrina Testi Melgarejo

Dissertations, Theses, and Capstone Projects

The theorization of trauma in literary studies emerged in the 1990s, evolving from its physiological origins to a multidisciplinary framework encompassing literature, psychology, and history. However, classical trauma theory, rooted in Western scholarship and focused on singular traumatic events, has been criticized for its limitations in addressing collective and ongoing trauma in non-Western contexts. This thesis responds to a call for a more inclusive approach to trauma studies, examining how multi-generational and cultural trauma is represented in non-Western postcolonial films and literature from the Global South, including works from the Philippines, Sri Lanka, Cuba, Angola, Mozambique, Vietnam, and Lebanon.

The …

Underlying Mechanisms Of Quantum Emission In Hexagonal Boron Nitride, Enrique Alejandro Mejia Iv

Dissertations, Theses, and Capstone Projects

Quantum emitters in hexagonal boron nitride (hBN) have emerged as promising candidates for advancing numerous quantum technologies. Visible-spectrum quantum emitters, in particular, have gained significant attention due to their exceptional properties, including high brightness, observable spin structure, and highly tunable emission wavelengths. However, several challenges hold back the practical implementation of hBN-based quantum emitters in technological applications—namely, the unknown physical structure of the emitters, susceptibility to spectral wandering and blinking, and limited understanding of how to control their broad spectral distribution.

In this dissertation, we investigate the collective properties of highly defective hBN. To address the key challenges, we develop …

Pharmacologic Management Of Heart Failure With Preserved Ejection Fraction (Hfpef) In Older Adults, Ashkan Hashemi, Min Ji Kwak, Parag Goyal

Faculty, Staff and Student Publications

There are several pharmacologic agents that have been touted as guideline-directed medical therapy for heart failure with preserved ejection fraction (HFpEF). However, it is important to recognize that older adults with HFpEF also contend with an increased risk for adverse effects from medications due to age-related changes in pharmacokinetics and pharmacodynamics of medications, as well as the concurrence of geriatric conditions such as polypharmacy and frailty. With this review, we discuss the underlying evidence for the benefits of various treatments in HFpEF and incorporate key considerations for older adults, a subpopulation that may be at higher risk for adverse drug …

Exploring Reciprocal Links Between Early Adolescent Coping And Internalizing Symptoms, Caitlyn Mytelka, Sarah C Narendorf, Elizabeth Baumler, Chiara Acquati, Jeff R Temple

Faculty, Staff and Student Publications

Introduction: The rising prevalence of depression and anxiety among adolescents is a public health concern. Early adolescence is a key developmental period to reduce risks for internalizing symptoms through primary prevention programs, yet additional research is needed on modifiable factors, such as coping skills, to target to mitigate risk factors. Therefore, we investigated the reciprocal link between coping style and internalizing symptoms among a racially/ethnically diverse sample of early adolescents (n = 1273) from 12 middle schools over 1 year.

Methods: We leveraged a longitudinal data set of a cluster, randomized trial of a preventive intervention from 12 middle schools …

Bringing Team Science To The Ambulatory Diagnostic Process: How Do Patients And Clinicians Develop Shared Mental Models?, Aubrey Samost-Williams, Eric J Thomas, Olivia Lounsbury, Scott I Tannenbaum, Eduardo Salas, Sigall K Bell

Faculty, Staff and Student Publications

The ambulatory diagnostic process is potentially complex, resulting in faulty communication, lost information, and a lack of team coordination. Patients and families have a unique position in the ambulatory diagnostic team, holding privileged information about their clinical conditions and serving as the connecting thread across multiple healthcare encounters. While experts advocate for engaging patients as diagnostic team members, operationalizing patient engagement has been challenging. The team science literature links improved team performance with shared mental models, a concept reflecting the team's commonly held knowledge about the tasks to be done and the expertise of each team member. Despite their proven …

Management Of Isolated Partial Acl Tears: A Survey Of International Acl Surgeons, Christopher S Frey, Kinsley J Pierre, Nicole S Pham, Geoffrey D Abrams, Seth L Sherman, Tim Spalding, Marc R Safran

Faculty, Staff and Student Publications

Background: Partial anterior cruciate ligament (ACL) tears, particularly injuries detected with magnetic resonance imaging (MRI) but stable on ligamentous examination, appear to be recognized more frequently; however, there remains no consensus management for this complex pathology.

Purpose: To present the results of a survey of a group of international ACL experts on the management of partial ACL injuries.

Study design: Survey study; Level of evidence, 5.

Methods: The ACL Study Group is an international group of orthopaedic surgeons with a special interest in the ACL. There are 169 members overall, with 135 clinically active surgeons. A branching logic survey was …

A Randomized, Double-Blind, Placebo-Controlled Trial Of Daxibotulinumtoxina For Injection For The Treatment Of Upper Limb Spasticity In Adults After Stroke Or Traumatic Brain Injury, Rashid Kazerooni

Faculty, Staff and Student Publications

Background: Intramuscular injection of botulinum toxin type A is a first-line pharmacotherapy for adults with upper limb spasticity (ULS). However, reemergence of symptoms within 12 weeks of treatment is common and longer-lasting treatments are needed.

Objective: To evaluate the efficacy and safety of three doses of DaxibotulinumtoxinA for Injection (DAXI) for treatment of ULS in adults with stroke or traumatic brain injury.

Intervention: Intramuscular injections of placebo (N = 24), DAXI 250 U (N = 22), DAXI 375 U (N = 19), or DAXI 500 U (N = 18) to the suprahypertonic muscle (SMG) and other muscle groups.

Design: Randomized, …

From Stable Teamwork To Dynamic Teaming In The Ambulatory Care Diagnostic Process

Faculty, Staff and Student Publications

Dynamic teaming is required whenever people must coordinate with one another in a fluid context, particularly when the fundamental structures of a team, such as membership, priorities, tasks, modes of communication, and location are in near-constant flux. This is certainly the case in the contemporary ambulatory care diagnostic process, where circumstances and conditions require a shifting cast of individuals to coordinate dynamically to ensure patient safety. This article offers an updated perspective on dynamic teaming commonly required during the ambulatory diagnostic process. Drawing upon team science, it clarifies the characteristics of dynamic diagnostic teams, identifies common risk points in the …

The Role Of Double-Zero-Event Studies In Evidence Synthesis: Evaluating Robustness Using The Fragility Index, Zelin Wang, Xing Xing, Eun-Young Mun, Chong Wu, Lifeng Lin

Faculty, Staff and Student Publications

Rationale: Zero-event counts are common in clinical studies, particularly when assessing rare adverse events. These occurrences can result from low event rates, short follow-up periods, and small sample sizes. When both intervention and control groups report zero events in a clinical trial, the study is referred to as a double-zero-event study, which presents methodological challenges for evidence synthesis. There has been ongoing debate about whether these studies should be excluded from evidence synthesis, as traditional two-stage meta-analysis methods may not estimate an effect size for them. Recent research suggests that these studies may still contain valuable clinical and statistical information. …

Positive Species Interactions Structure Rhodolith Bed Communities At A Global Scale, Fabio Bulleri, Nadine Schubert, Jason M. Hall-Spencer, Daniela Basso, Heidi L. Burdett, Ronaldo B. Francini-Filho, Jacques Grall, Paulo A. Horta, Nicholas A. Kamenos, Sophie Martin, Matteo Nannini, Pedro Neves, Irene Olivé, Viviana Peña, Federica Ragazzola, Cláudia Ribeiro, Eli Rinde, Marina Sissini, Fernando Tuya, João Silva

School of Biological and Marine Sciences

Rhodolith beds are diverse and globally distributed habitats. Nonetheless, the role of rhodoliths in structuring the associated species community through a hierarchy of positive interactions is yet to be recognised. In this review, we provide evidence that rhodoliths can function as foundation species of multi-level facilitation cascades and, hence, are fundamental for the persistence of hierarchically structured communities within coastal oceans. Rhodoliths generate facilitation cascades by buffering physical stress, reducing consumer pressure and enhancing resource availability. Due to large variations in their shape, size and density, a single rhodolith bed can support multiple taxonomically distant and architecturally distinct habitat-forming species, …

Exploring Key Factors Influencing Depressive Symptoms Among Middle-Aged And Elderly Adult Population: A Machine Learning-Based Method, Ngoc Doan Thu Tran, Yi Zhen Tan, Sapphire Lin, Fang Zhao, Yee Sien Ng, Dong Ma, Jeonggil Ko, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Objective: This paper aims to investigate the key factors, including demographics, socioeconomics, physical wellbeing, lifestyle, daily activities and loneliness that can impact depressive symptoms in the middle-aged and elderly population using machine learning techniques. By identifying the most important predictors of depressive symptoms through the analysis, the findings can have important implications for early depression detection and intervention. Participants: For our cross-sectional study, we recruited a total of 976 volunteers, with a specific focus on individuals aged 50 and above. Each participant was requested to provide their demographic, socioeconomic information and undergo several physical health tests. Additionally, they were asked …

The Role Of Surprisal In Issue Trackers, James Caddy, Christoph Treude, Markus Wagner, Earl T. Barr

Research Collection School Of Computing and Information Systems

Context: Software development creates and relies on a large volume of information, yet the volume of this information can make it challenging for developers to maintain an overview of all goings-on that a team and external actors contribute to a project. We posit that unexpected or “surprising” events could serve as important signposts amidst this information overload. These unexpected events may indicate underlying anomalies or emergent situations that require immediate attention. To explore this premise, our study leverages the concept of ‘surprisal’ from information theory to identify and quantify these unusual occurrences from the issues and pull requests of popular …

Ptm4tag+: Tag Recommendation Of Stack Overflow Posts With Pre-Trained Models, Junda He, Bowen Xu, Zhou Yang, Donggyun Han, Chengran Yang, Jiakun Liu, Zhipeng Zhao, David Lo

Research Collection School Of Computing and Information Systems

Stack Overflow is one of the most influential Software Question & Answer (SQA) websites, hosting millions of programming-related questions and answers. Tags play a critical role in efficiently organizing the contents on Stack Overflow and are vital to support various site operations, such as querying relevant content. Poorly chosen tags often lead to issues such as tag ambiguity and tag explosion. Therefore, a precise and accurate automated tag recommendation technique is needed. Inspired by the recent success of pre-trained models (PTMs) in natural language processing (NLP), we present PTM4Tag+, a tag recommendation framework for Stack Overflow posts that utilize PTMs …

Exploring & Exploiting High-Order Graph Structure For Sparse Knowledge Graph Completion, Tao He, Ming Liu, Yixin Cao, Zekun Wang, Zihao Zheng, Bing Qin

Research Collection School Of Computing and Information Systems

Sparse Knowledge Graph (KG) scenarios pose a challenge for previous Knowledge Graph Completion (KGC) methods, that is, the completion performance decreases rapidly with the increase of graph sparsity. This problem is also exacerbated because of the widespread existence of sparse KGs in practical applications. To alleviate this challenge, we present a novel framework, LR-GCN, that is able to automatically capture valuable long-range dependency among entities to supplement insufficient structure features and distill logical reasoning knowledge for sparse KGC. The proposed approach comprises two main components: a GNN-based predictor and a reasoning path distiller. The reasoning path distiller explores high-order graph …

Bridging Expert Knowledge With Deep Learning Techniques For Just-In-Time Defect Prediction, Xin Zhou, Donggyun Han, David Lo

Research Collection School Of Computing and Information Systems

Just-In-Time (JIT) defect prediction aims to automatically predict whether a commit is defective or not, and has been widely studied in recent years. In general, most studies can be classified into two categories: 1) simple models using traditional machine learning classifiers with hand-crafted features, and 2) complex models using deep learning techniques to automatically extract features from commit contents. Hand-crafted features used by simple models are based on expert knowledge but may not fully represent the semantic meaning of the commits. On the other hand, deep learning-based features used by complex models represent the semantic meaning of commits but may …

Proactive Conversational Ai: A Comprehensive Survey Of Advancements And Opportunities, Yang Deng, Lizi Liao, Wenqiang Lei, Grace Hui Yang, Wai Lam, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Dialogue systems are designed to offer human users social support or functional services through natural language interactions. Traditional conversation research has put significant emphasis on a system's response-ability, including its capacity to understand dialogue context and generate appropriate responses. However, the key element of proactive behavior-a crucial aspect of intelligent conversations-is often overlooked in these studies. Proactivity empowers conversational agents to lead conversations towards achieving pre-defined targets or fulfilling specific goals on the system side. Proactive dialogue systems are equipped with advanced techniques to handle complex tasks, requiring strategic and motivational interactions, thus representing a significant step towards artificial general …

Wf-Ppg: A Wrist-Finger Dual-Channel Dataset For Studying The Impact Of Contact Pressure On Ppg Morphology, Matthew Yiwen Ho, Hung Manh Pham, Aaqib Saeed, Dong Ma

Research Collection School Of Computing and Information Systems

Photoplethysmography (PPG) is a simple optical technique widely used in wearable devices for continuous cardiac health monitoring. However, the quality of PPG signals, particularly their morphology, is influenced by the contact pressure between the skin and the sensor. This variability in signal quality complicates complex tasks that rely on high-quality signals, such as blood pressure and heart rate variability estimation, making them less reliable or even impossible. To address this issue, we present a novel dataset (termed WF-PPG) comprising PPG signals from the wrist measured under varying contact pressures, along with high-quality PPG signals from the fingertip captured simultaneously. Data …

Loco: Low-Bit Communication Adaptor For Large-Scale Model Training, Xingyu Xie, Zhijie Lin, Kim-Chuan Toh, Pan Zhou

Research Collection School Of Computing and Information Systems

To efficiently train large-scale models, low-bit gradient communication compresses full-precision gradients on local GPU nodes into low-precision ones for higher gradient synchronization efficiency among GPU nodes. However, it often degrades training quality due to compression information loss. To address this, we propose the Low-bit Communication Adaptor (LoCo), which compensates gradients on local GPU nodes before compression, ensuring efficient synchronization without compromising training quality. Specifically, LoCo designs a moving average of historical compensation errors to stably estimate concurrent compression error and then adopts it to compensate for the concurrent gradient compression, yielding a less lossless compression. This mechanism allows it to …

Qultsf: Long-Term Time Series Forecasting With Quantum Machine Learning, Hari Hara Suthan Chittoor, Paul Robert Griffin, Ariel Neufeld, Jayne Thompson, Mile Gu

Research Collection School Of Computing and Information Systems

Long-term time series forecasting (LTSF) involves predicting a large number of future values of a time series based on the past values. This is an essential task in a wide range of domains including weather forecasting, stock market analysis and disease outbreak prediction. Over the decades LTSF algorithms have transitioned from statistical models to deep learning models like transformer models. Despite the complex architecture of transformer based LTSF models ‘Are Transformers Effective for Time Series Forecasting? (Zeng et al., 2023)’ showed that simple linear models can outperform the state-of-the-art transformer based LTSF models. Recently, quantum machine learning (QML) is evolving …

Siniel: Distributed Privacy-Preserving Zksnark, Yunbo Yang, Yuejia Cheng, Kailun Wang, Xiaoguo Li, Jianfei Sun, Jiachen Shen, Xiaolei Dong, Zhenfu Cao, Guomin Yang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Zero-knowledge Succinct Non-interactive Argument of Knowledge (zkSNARK) is a powerful cryptographic primitive, in which a prover convinces a verifier that a given statement is true without leaking any additional information. However, existing zkSNARKs suffer from high computation overhead in the proof generation. This limits the applications of zkSNARKs, such as private payments, private smart contracts, and anonymous credentials. Private delegation has become a prominent way to accelerate proof generation. In this work, we propose Siniel, an efficient private delegation framework for zkSNARKs constructed from polynomial interactive oracle proof (PIOP) and polynomial commitment scheme (PCS). Our protocol allows a computationally limited …

Impact Tracing: Identifying The Culprit Of Misinformation In Encrypted Messaging Systems, Zhongming Wang, Tao Xiang, Xiaoguo Li, Biwen Chen, Guomin Yang, Chuan Ma, Robert H. Deng

Research Collection School Of Computing and Information Systems

Encrypted messaging systems obstruct content moderation, although they provide end-to-end security. As a result, misinformation proliferates in these systems, thereby exacerbating online hate and harassment. The paradigm of “Reporting-then-Tracing” shows great potential in mitigating the spread of misinformation. For instance, message traceback (CCS’19) traces all the dissemination paths of a message, while source tracing (CCS’21) traces its originator. However, message traceback lacks privacy preservation for non-influential users (e.g., users who only receive the message once), while source tracing maintains privacy but only provides limited traceability. In this paper, we initiate the study of impact tracing. Intuitively, impact tracing traces influential …

Seven Hci Grand Challenges Revisited: Five-Year Progress, Constantine Stephanidis, Gavriel Salvendy, Margherita Antona, Vincent G Duffy, Qin Gao, Waldemar Karwowski, Fiona Nah, Stavroula Ntoa, Pei-Luen Patrick Rau, Keng Siau, Jia Zhou

Research Collection School Of Computing and Information Systems

Motivated by the rapid technological advancements achieved in the last five years, and the pervasiveness of Artificial Intelligence, the paper investigates the evolving role of Human-Computer Interaction and revisits the seven grand challenges outlined in 2019: human-technology symbiosis, human-environment interactions, ethics, privacy and security, well-being, health and eudaimonia, accessibility and universal access, learning and creativity, and social organization and democracy. Through literature analysis, the paper reevaluates the status of each challenge and highlights emerging requirements. Key findings reveal the widespread impact of Artificial Intelligence across all domains and emphasize the need for improved AI transparency, alignment with human values, and …

Hotpatching On The Fly: Mitigating Drone Incidents Arising From Incorrect Configuration, Ruidong Han, Juanru Li, Zhuo Ma, David Lo, Arash Shaghaghi, Jianfeng Ma, Siqi Ma

Research Collection School Of Computing and Information Systems

Manufacturers offer adjustable control parameters for flight control systems to accommodate diverse environments and missions. To ensure flight safety, they also develop established boundaries, i.e., range specifications for parameter values. However, even when the configuration parameters fall within the prescribed manufacturer range, they could still lead to instability or even severe incidents like crashes, which are referred to as Range Specification Bugs. Prior research has suggested shrinking the range of parameter values to protect drones from the adverse effects of such bugs. However, narrowing the range of parameters may only reduce the probability of errors and could potentially limit the …

Advisor Satisfaction To Support Online Student Retention, Erica K. Whiddon

Electronic Theses and Dissertations

In this dissertation, the researcher explored the relationship between satisfaction with academic advising and online student retention. Online student retention is a critical issue in the context of increasing competition for students in higher education institutions. The specific problem was that online students have lower retention rates, and the reasons students typically select online degree programs are also the reasons they drop out of their degree programs. The purpose was to identify whether students’ reported satisfaction with their advisors mediated the relationship between the existence of external personal life factors and retention. A quantitative nonexperimental causal-comparative and correlational research design …

Consumption Responses To Income Shocks Through Lottery Winning, Seonghoon Kim, Kanghyock Koh

Research Collection School Of Economics

We study the effects of lottery winning on consumption spending using newly available household survey data in Singapore. We find strong consumption responses to a transitory income shock via lottery wins. Lottery winners spend about half of their prizes within 12 months of winning. We show that consumption responses are stronger among households with more binding liquidity constraints and less risk aversion, which is consistent with the standard life-cycle model. The strong consumption response suggests that fiscal stimulus policies or other public transfer programs could be an effective means of boosting consumption spending of the economy in the short run.