Digital Commons Network^™

Dgl: Dynamic Global-Local Information Aggregation For Scalable Vrp Generalization With Self-Improvement Learning, Yubin Xiao, Yuesong Wu, Rui Cao, Di Wang, Zhiguang Cao, Xuan Wu, Peng Zhao, Yuanshu Li, You Zhou, Yuan Jiang

Research Collection School Of Computing and Information Systems

The Vehicle Routing Problem (VRP) is a critical combinatorial optimization problem with wide-reaching real-world applications, particularly in logistics, transportation. While neural network-based VRP solvers have shown impressive results on test instances similar to training data, their performance often degrades when faced with varying scales and unseen distributions, limiting their practical applicability. To overcome these limitations, we introduce DGL (Dynamic Global-Local Information Aggregation), a novel model that combines global and local information to effectively solve VRPs. DGL dynamically adjusts local node selections within a localized range, capturing local invariance across problems of different scales and distributions, thereby enhancing generalization. At the …

Coupling Category Alignment For Graph Domain Adaptation, Nan Yin, Xiao Teng, Zhiguang Cao, Mengzhu Wang

Research Collection School Of Computing and Information Systems

Graph domain adaptation (GDA), which transfers knowledge from a labeled source domain to an unlabeled target graph domain, attracts considerable attention in numerous fields. However, existing methods commonly employ message-passing neural networks (MPNNs) to learn domain-invariant representations by aligning the entire domain distribution, inadvertently neglecting category-level distribution alignment and potentially causing category confusion. To address the problem, we propose an effective framework named Coupling Category Alignment (CoCA) for GDA, which effectively addresses the category alignment issue with theoretical guarantees. CoCA incorporates a graph convolutional network branch and a graph kernel network branch, which explore graph topology in implicit and explicit …

Map As A By-Product: Collective Landmark Mapping From Imu Data And User-Provided Texts In Situated Tasks, Ryo Yonetani, Kotaro Hara

Research Collection School Of Computing and Information Systems

This paper presents Collective Landmark Mapper, a novel map-as-a-by-product system for generating semantic landmark maps of indoor environments. Consider users engaged in situated tasks that require them to navigate these environments and regularly take notes on their smartphones. Collective Landmark Mapper exploits the smartphone's IMU data and the user's free text input during these tasks to identify a set of landmarks encountered by the user. The identified landmarks are then aggregated across multiple users to generate a unified map representing the positions and semantic information of all landmarks. In developing the proposed system, we focused specifically on retail applications and …

Towards Multimodal Emotional Support Conversation Systems, Yuqi Chu, Lizi Liao, Zhiyuan Zhou, Chong-Wah Ngo, Richang Hong

Research Collection School Of Computing and Information Systems

The integration of conversational artificial intelligence (AI) into mental health care promises a new horizon for therapist-client interactions, aiming to closely emulate the depth and nuance of human conversations. Despite the potential, the current landscape of conversational AI is markedly limited by its reliance on single-modal data, constraining the systems’ ability to empathize and provide effective emotional support. This limitation stems from a paucity of resources that encapsulate the multimodal nature of human communication essential for therapeutic counseling. To address this gap, we introduce the Multimodal Emotional Support Conversation (MESC) dataset, a first-of-its-kind resource enriched with comprehensive annotations across text, …

Conv4rec: A 1‑By‑1 Convolutional Autoencoder For User Profiling Through Joint Analysis Of Implicit And Explicit Feedbacks, Antoine Ledent, Petr Kasalický, Rodrigo Alves, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

We introduce a new convolutional autoencoder architecture for user modeling and recommendation tasks with several improvements over the state of the art. First, our model has the flexibility to learn a set of associations and combinations between different interaction types in a way that carries over to each user and item. Second, our model is able to learn jointly from both the explicit ratings and the implicit information in the sampling pattern (which we refer to as ”implicit feedback”). It can also make separate predictions for the probability of consuming content and the likelihood of granting it a high rating …

Rethinking Cognitive Complexity For Unit Tests: Toward A Readability-Aware Metric Grounded In Developer Perception, Wendkûuni C. Ouédraogo, Yinghua Li, Xueqi Dang, Xin Zhou, Anil Koyuncu, Jacques Klein, David Lo, Tegawendé F. Bissyandé

Research Collection School Of Computing and Information Systems

Automatically generated unit tests-from searchbased tools like EvoSuite or LLMs-vary significantly in structure and readability. Yet most evaluations rely on metrics like Cyclomatic Complexity and Cognitive Complexity, designed for functional code rather than test code. Recent studies have shown that SonarSource's Cognitive Complexity metric assigns nearzero scores to LLM-generated tests, yet its behavior on EvoSuitegenerated tests and its applicability to test-specific code structures remain unexplored. We introduce CCTR, a Test-Aware Cognitive Complexity metric tailored for unit tests. CCTR integrates structural and semantic features like assertion density, annotation roles, and test composition patterns-dimensions ignored by traditional complexity models but critical for …

Flow, Immersion, And Presence: Creating Virtual Reality And Engagement In The Era Of Ubiquitous And Intelligent Technologies, Yi Maggie Guo, Fiona Fui-Hoon Nah, Nannan Xi, Marshall Scott Poole

Research Collection School Of Computing and Information Systems

Researchers use the concepts of flow, immersion, and presence to explain the usage of and engagement (e.g., cognitive absorption) with information technology. In this special issue, we showcase four papers on empirical investigations of flow and immersion, their antecedents, and their outcomes. These papers address research questions that range from investigating the antecedents and consequences of immersion in head-mounted displays of virtual reality, designing for the flow experience in extended reality, studying factors influencing user engagement in the metaverse, and identifying adverse effects of work-related flow. We also provide directions and suggestions for future research.

Improving Co-Decoding Based Security Hardening Of Code Llms Leveraging Knowledge Distillation, Dong Li, Shanfu Shu, Meng Yan, Zhongxin Liu, Chao Liu, Xiaohong Zhang, David Lo

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have been widely adopted by developers in software development. However, the massive pretraining code data is not rigorously filtered, allowing LLMs to learn unsafe coding patterns. Several prior studies have demonstrated that code LLMs tend to generate code with potential vulnerabilities. The widespread adoption of intelligent programming assistants poses a significant threat to the software development process. Existing approaches to mitigating this risk primarily involve constructing secure data that are free of vulnerabilities and then retraining or fine-tuning the models. However, such an effort is resource intensive and requires significant manual supervision. When the model parameters …

Finding Safety Violations Of Ai-Enabled Control Systems Through The Lens Of Synthesized Proxy Programs, Jieke Shi, Zhou Yang, Junda He, Bowen Xu, Dongsun Kim, Donggyun Han, David Lo

Research Collection School Of Computing and Information Systems

Given the increasing adoption of modern AI-enabled control systems, ensuring their safety and reliability has become a critical task in software testing. One prevalent approach to testing control systems is falsification, which aims to find an input signal that causes the control system to violate a formal safety specification using optimization algorithms. However, applying falsification to AI-enabled control systems poses two significant challenges: (1) it requires the system to execute numerous candidate test inputs, which can be time-consuming, particularly for systems with AI models that have many parameters, and (2) multiple safety requirements are typically defined as a conjunctive specification, …

Exploring Parameter-Efficient Fine-Tuning Techniques For Code Generation With Large Language Models, Martin Weyssow, Xin Zhou, Kisub Kim, David Lo, Houari A. Sahraoui

Research Collection School Of Computing and Information Systems

Large language models (LLMs) demonstrate impressive capabilities to generate accurate code snippets given natural language intents in a zero-shot manner, i.e., without the need for specific fine-tuning. While prior studies have highlighted the advantages of fine-tuning LLMs, this process incurs high computational costs, making it impractical in resource-scarce environments, particularly for models with billions of parameters. To address these challenges, previous research explored in-context learning (ICL) and retrieval-augmented generation (RAG) as strategies to guide the LLM generative process with task-specific prompt examples. However, ICL and RAG introduce inconveniences, such as the need for designing contextually relevant prompts and the absence …

Ponzilens+: Visualizing Bytecode Actions For Smart Ponzi Scheme Identification, Xiaolin Wen, Tai D. Nguyen, Shaolun Ruan, Qiaomu Shen, Jun Sun, Feida Zhu, Yong Wang

Research Collection School Of Computing and Information Systems

With the prevalence of smart contracts, smart Ponzi schemes have become a common fraud on blockchain and have caused significant financial loss to cryptocurrency investors in the past few years. Despite the critical importance of detecting smart Ponzi schemes, a reliable and transparent identification approach adaptive to various smart Ponzi schemes is still missing. To fill the research gap, we first extract semantic-meaningful actions to represent the execution behaviors specified in smart contract bytecodes, which are derived from a literature review and in-depth interviews with domain experts. We then propose PonziLens+, a novel visual analytic approach that provides an intuitive …

Managing Rumors On Electronic Interaction Platforms: How Management Responses Affect Investor Reaction, Runyu Wang, Zili Zhang, Keng Siau, Ziqiong Zhang

Research Collection School Of Computing and Information Systems

This study investigates how listed firms respond to investors’ rumor-related inquiries and examines the impact of these responses on investor reactions, as indicated by subsequent daily abnormal stock returns (ARs). Using a unique dataset of question-and-answer (Q&A) interactions from China’s major e-interaction platforms, established by the stock exchanges, our study provides insights into regulated firm-investor communications in a structured Q&A setting. Unlike informal social media channels, these platforms enable official responses from firm representatives, typically board secretaries, under direct regulatory oversight. By analyzing rumor-related Q&A pairs with regression models and several robustness checks, we find that firms can benefit from …

Shortcuts Everywhere And Nowhere: Exploring Multi-Trigger Backdoor Attacks, Yige Li, Jiabo He, Hanxun Huang, Jun Sun, Xingjun Ma, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Backdoor attacks have become a significant threat to the pre-training and deployment of deep neural networks (DNNs). Although numerous methods for detecting and mitigating backdoor attacks have been proposed, most rely on identifying and eliminating the “shortcut” created by the backdoor, which links a specific source class to a target class. However, these approaches can be easily circumvented by designing multiple backdoor triggers that create shortcuts everywhere and therefore nowhere specific. In this study, we explore the concept of Multi-Trigger Backdoor Attacks (MTBAs), where multiple adversaries leverage different types of triggers to poison the same dataset. By proposing and investigating …

Robface: A Test Suite For Efficient Robustness Evaluation Of Face Recognition Systems, Ruihan Zhang, Jun Sun

Research Collection School Of Computing and Information Systems

Face recognition is a widely used authentication technology in practice, where robustness is required. It is thus essential to have an efficient and easy-to-use method for evaluating the robustness of (possibly third-party) trained face recognition systems. Existing approaches to evaluating the robustness of face recognition systems are either based on empirical evaluation (e.g., measuring attacking success rate using state-of-the-art attacking methods) or formal analysis (e.g., measuring the Lipschitz constant). While the former demands significant user efforts and expertise, the latter is extremely time-consuming. In pursuit of a comprehensive, efficient, easy-to-use, and scalable estimation of the robustness of face recognition systems, …

Bridging The Digital Skills Gap: A Comparative Study Of Employability Readiness Among Tourism Students And Professionals In Malaysia, Asif Khurshid Mian, Fraz Arshed Butt, Omar Sajid

Journal of Global Hospitality and Tourism

The increasing digitalisation of the tourism industry has introduced new expectations for workforce competencies, particularly in developing economies like Malaysia. The present study investigates how three core digital competencies, i.e. digital literacy, platform/tool awareness, and technology readiness, influence employability readiness among two key groups including final-year tourism students and in-service professionals. Drawing on Human Capital Theory and the Technology Readiness Index, the research applies Partial Least Squares Structural Equation Modelling (PLS-SEM) to examine 350 responses collected through purposive sampling. Results confirm that all three competencies positively influence employability readiness, with platform/tool awareness exerting the strongest effect. Multi-group analysis reveals that …

Applying The Synergy Of Experience Accounting And Service Dominant Logic To Rank Customer Experiences In The Mainstream Cruising, Ganna Demydyuk, Mats Carlbäck

Journal of Global Hospitality and Tourism

This study analyzes how service-related experiences influence customer satisfaction and perceived value for money in the cruise industry. By integrating Service-Dominant Logic (S-D-L) and Experience Accounting (EA), it aims to support the development of customer-centric performance systems for managerial decision making in the all-inclusive hospitality sector. This is the first empirical study to merge data from three perspectives in service-for-service exchanges: customer review ratings from online platforms, ship-level operational characteristics, and financial metrics from corporate reports. This integrated approach allows for a holistic evaluation of the service ecosystem and cocreation of value onboard cruise ships. A quantitative analysis was conducted …

Nurses’ Knowledge About Assisted Reproductive Methods And Their Awareness About It In Potential Immune-Related Outcomes Of Conceived Children, Salma Abd-Elatty Moawed, Abdallah Ahmed Said

Nursing

Abstract A rising worldwide health concern, infertility is impacted by a number of environmental and lifestyle factors. With cutting-edge methods like intrauterine insemination, intracytoplasmic sperm injection, and in vitro fertilization, assisted reproductive technology gives infertile couples hope. Because they provide clinical care, education, and emotional support before, during, and after assisted reproductive technology procedures, nurses are essential to its success. The purpose of this study is to assess nurses’ knowledge and awareness about assisted reproductive methods and the immune outcomes among the resulting children. A structured interview questionnaire will be used to gather data from 130 nurses as part of …

Blending Informing Literacy And Visual Literacy: Instructional Vignettes In Art, Architecture, And Design, Stephanie Beene, Sara Schumacher, Dana Statton Thompson, Mary Wegmann

University Libraries & Learning Sciences Faculty and Staff Publications

The ACRL Framework for Visual Literacy in Higher Education (Framework for Visual Literacy), based on empirical research into the trends, opportunities, and challenges facing the field of visual literacy in the twenty-first century,1 was codified in April 2022 and is an adaptable document to help learners grow their visual literacy competencies. In this chapter, written by four of the task force members charged with the creation of the Framework for Visual Literacy, we examine the relationship between the four themes in the Framework for Visual Literacy and the six frames of the ACRL Framework for Information Literacy for Higher Education …

Neutrosophic-Based Cephalometric Analysis For Egyptian Population Using Novel Software, Nagham Ahmed Abdelmegeed, Amal F.Abdel-Gawad, Mohamed Alaa Fahmy El-Ghamry

Neutrosophic Sets and Systems

No abstract provided.

Optimizing Fire Detection In Remote Sensing Imagery For Edge Devices: A Quantization-Enhanced Hybrid Deep Learning Model, Syed Muhammad Salman Bukhari, Nadia Dahmani, Sujan Gyawali, Muhammad Hamza Zafar, Filippo Sanfilippo, Kiran Raja

All Works

Wildfires are increasing in frequency and severity, presenting critical challenges for timely detection and response, particularly in remote or resource-limited environments. This study introduces the Inception-ResNet Transformer with Quantization (IRTQ), a novel hybrid deep learning (DL) framework that integrates multi-scale feature extraction with global attention and advanced quantization. The proposed model is specifically optimized for edge deployment on platforms such as unmanned aerial vehicles (UAVs), offering a unique combination of high accuracy, low latency, and compact memory footprint. The IRTQ model achieves 98.9% accuracy across diverse datasets and shows strong generalization through cross-dataset validation. Quantization significantly reduces the parameter count …

Development Of The Negative Attitudes Toward Nonbinary Individuals Scale, Jenna Sue Lehmann

Tennessee State University Alumni Theses and Dissertations

Research within the field of psychology examining the experiences of transgender individuals and prejudice toward transgender individuals has increased in recent history alongside the conscious awareness of transgender individuals within the United States. The research that has been conducted has primarily focused on transgender individuals broadly as a group on binary transgender individuals. As, such measures of prejudice toward these groups have been developed and validated. Although the study of nonbinary experiences and prejudice is developing, there has been no extant measure of prejudice toward nonbinary individuals specifically. A measure of prejudice toward this group is needed to (1) examine …

Scspatialsim: A Simulator Of Spatial Single-Cell Molecular Data, Alex C. Soupir, Julia Wrobel, Jordan H. Creed, Oscar E. Ospina, Christopher M. Wilson, Brandon J. Manley, Lauren C. Peres, Brooke L. Fridley

Manuscripts, Articles, Book Chapters and Other Papers

The increasing use of spatial molecular technologies such as multiplex immunofluorescence (mIF) and spatial transcriptomics (SRT) has driven the need for robust statistical methods to analyze the spatial architecture of tissues. However, a lack of consensus on “gold standard” approaches present challenges for benchmarking and comparison. To address this gap, we developed “scSpatialSIM”, an R package for simulating biologically realistic spatial single-cell molecular data. “scSpatialSIM” enables users to efficiently simulate single-cell spatial patterns without requiring reference datasets, incorporating features such as cell clustering, cell co-localization, tissue compartments, and tissue holes. Additionally, the package supports simulation of both categorical data (e.g., …

Impostor Phenomenon, Psychological Safety, And The Intent To Leave Of Novice Pa Faculty, Barbara J. Quillin

Electronic Theses and Dissertations

The growing healthcare demands of the aging population in the United States, along with the growth of physician assistant (PA) educational programs, has created a pressing need for qualified PA educators. This study examined the role of impostor phenomenon and psychological safety in shaping PA faculty members’ intent to leave. Grounded in the job demands-resources framework, the research explored how individual psychological experiences and perceptions of the organizational climate relate to faculty turnover intentions in PA education. This study aimed to provide PA program administrators with information that may reduce faculty attrition and improve the overall well-being of novice faculty. …

Underrepresentation Of African American Women Superintendents In The Public Schools Of Texas: Descriptions Of Their Lived Experiences, Shani R. Wyllie

Electronic Theses and Dissertations

The problem addressed through this study was the underrepresentation of African American women superintendents in the public-school districts of Texas, despite women making up a majority of the public-school workforce. The purpose of this transcendental phenomenological study was to describe the lived experiences of African American women superintendents regarding the support and barriers they encountered as they navigated their journeys to the position of public school district superintendent in Texas. The study was grounded in the Black feminist thought framework. Five semistructured interviews were conducted with currently serving African American women superintendents in Texas. The participants had been in the …

Romania: ‘A Country Is Worth More Than Its Gold’: Activists Defeat Canadian Mining Goliath. In, Roxana Maiorescu

Emerson Authors, Researchers, & Creators

For 25 years, Romanians fought to preserve Rosia Montana, a region whose gold and silver amount to 20 billion euros. Their victory was delivered in 2024, as the International Center for Settlement of Investment Disputes in Washington, DC ruled against the Canadian company that aimed to explore the mine. This analysis sheds light on political instability, perceived government corruption, and foreign intrusion, all of which led to intense and monthslong protests that Romania hadn’t seen since its 1989 revolution, when it liberated itself from communism. This case represents a David vs. Goliath-like story, in which a handful of poor families, …

Systematic Review And Evidence Gap Mapping Of Alzheimer's Disease Biomarker Studies In Those With Intellectual And Developmental Disability, Lubnaa B. Abdullah, Ney Alex Alliey, Emma Elizondo, Ney Alliey Rodriguez, Gladys Maestre, James Hall

School of Medicine Publications

There are a relatively small number of investigations into brain aging in those with intellectual and developmental disability (I/DD). This project seeks to (1) characterize the internationally available multi-omics Alzheimer's disease (AD) biomarker studies including those with I/DD, and (2) discuss future research directions. PubMed, Web of Science, and Scopus were searched under the following criteria: cross-sectional or longitudinal AD-omics studies on adults (18 +) with I/DD. 532 studies were identified, 186 studies were evaluated for full-text, 79 studies were excluded, and 117 studies were extracted. Most biological specimens were analyzed in blood, plasma, or serum. Metabolomics, hormonomics, and transcriptomics …

Horses And The Transition From Feudalism To Capitalism., Thomas E. Lambert

Faculty and Staff Scholarship

Many scholarly articles and books have been written about the transition from feudalism to capitalism over the decades. The various points of views on what is the “main driver” or “prime mover” of the transition have been debated in various forums by historians and economic historians with a different major factor being advocated by different proponents or schools of thought. This paper tries to offer another analysis of how the horse could have been an important “means to an end” in the development of capitalism, and this analysis possibly can lead to support for more than one view of what …

Variational Temporal Deconfounder Network For Individualized Treatment Effect Estimation With Longitudinal Observational Data, Hao Dai, Yu Huang, Yuxi Liu, Xing He, Jingchuan Guo, Mattia Prosperi, Jiang Bian

Faculty, Staff and Student Publications

Objective: By leveraging real-world electronic health record (EHR) data, this study set out to estimate individualized treatment effects (ITE) in longitudinal observational settings to advance personalized medicine, addressing key challenges that are often observed in real-world clinical scenarios and pose statistical challenges, including hidden confounding and dynamic treatment regimens.

Methods: We propose the Variational Temporal Deconfounder Network (VTDNet), a novel framework designed to account for time-varying hidden confounding using a variational recurrent transformer-based autoencoder. Specifically, VTDNet comprises three critical components: a temporal Encoder-Decoder structure to capture hidden representation, a Treatment Block that captures interdependencies among multiple treatments, and a Potential …

Sex Differences In The Treatment With Pcsk9 Monoclonal Antibodies- Real World Experience From A Dedicated Preventive Cardiology Clinic, Lital Hodeda, Alon Eisen, Aviad Rotholz, Ran Kornowski, Chen Gurevitz

Faculty, Staff and Student Publications

Purpose: Proprotein convertase subtilisin/kexin type 9 monoclonal antibodies (PCSK9 mAb) lower low-density lipoprotein cholesterol (LDL-C) levels and reduce atherosclerotic cardiovascular disease (ASCVD). Data regarding sex differences in PCSK9 mAb treatment remain lacking. This study examines sex differences in patients' characteristics, indications, efficacy, and safety of PCSK9 mAb treatment.

Methods: Retrospective study based on data from the Preventive Cardiology and Lipids Clinic in Rabin Medical Center on patients prescribed with PCSK9 mAb. Collected data included medical background, medications, indications and laboratory data, analyzed by sex.

Results: 246 patients were included (mean age 67y, ASCVD 78.8 %, mean baseline LDL-C 128.2 mg/dL). …

Nocturnal Foraging By Great Blue Heron (Ardea Herodias) And Roseate Spoonbill (Platalea Ajaja), Laura E. Josler, Johnny E. Owens, Sarrah E. Bristol, Leo N. Dutkewych, Abigail R. Kauke, Signe E. Renstrom, Ben G. Sheffield, Madelyne E. Vashaw, Avery J. Nesbitt, Melia K. Paat, Timothy D. Bransford, Elizabeth A. Forys

Florida Field Naturalist

The Great Blue Heron (Ardea herodias) and Roseate Spoonbill (Platalea ajaja) are long-legged wading birds that can forage throughout a 24-hour cycle. Nocturnal foraging enables these species to take advantage of optimal foraging conditions and reduced competition. This study aims to investigate how environmental factors influence the nocturnal foraging behavior of these species. To monitor foraging activity, we deployed 17-18 infrared cameras from dusk until dawn from 4 October 2023 to 24 July 24 2024, covering two sampling periods across different habitats within Fort De Soto County Park, a barrier island complex in Tampa Bay, Florida. We compared the frequency …