Digital Commons Network^™

Book Review: Emplacing Globalisation: Contextualising Mission In Settings Of People, Places And Processes By John Cheong And Jonathan Ro, David H. Campbell

Great Commission Research Journal

No abstract provided.

Book Review: Game Of Pulpits: The 7 Voices Vying For The Kingdom - Who Will Win & Why By Gary Comer, Lavern Brown

Great Commission Research Journal

No abstract provided.

Book Review: The American Religious Landscape By Ryan Burge, Derek Maxson

Great Commission Research Journal

No abstract provided.

About The Great Commission Research Network Spring 2026, David R. Dunaetz

Great Commission Research Journal

No abstract provided.

The Effectiveness Of The Educational Program “Istedamah” (Sustainability) Based On Green School Principles In Shaping Basic Education Students’ Perceptions Of Sustainable Development Dimensions And Their Practices In Achieving Carbon Neutrality In The School Environment In The Sultanate Of Oman, Huda Mubarak Al Dayri, Abdullah. K. Ambusaidi

Journal of Educational and Psychological Studies

The study aimed to identify the effectiveness of “ Istedamah” educational programme, which is based on green school principals, in promoting the perceptions of sustainable development dimensions and their practices related carbon neutrality among basic education students in the Sultanate of Oman. The study used quasi-experimental approach based on one group pre- and post -test design. The sample consisted of 106 male and female students selected randomly from schools that apply green school project. Two tools were used to gather data: A scale of students’ perceptions of the dimensions of sustainable development, (consisted of 26 statements) and practices for achieving …

Comparative Analysis Of Traffic Impact Study Accuracy Using Turning Movement Volume Counts., Kathryn Riopel

Master of Engineering Theses

Traffic forecasting and modeling has been a significant subject of debate within the transportation sector as of the last decade. Transportation agencies and planners use traffic forecasting and modeling in order to predict current and future transportation needs, as well as the impacts of proposed developments. In particular, state departments of transportation (DOTs) and city level agencies often require developers to conduct Traffic Impact Studies (TISes) in order to gauge necessary transport network enhancements to handle new demand from proposed developments. The standards by which these TISes are conducted and judged varies widely, but primarily consists of existing traffic counts, …

Developing 'A Guide To Agricultural Education Advisory Committees: Development, Uses, And Transitions', Christine Schuler

Department of Agricultural Leadership, Education, and Communication: Dissertations, Theses, and Student Research

This project developed a practical guide to support agricultural education advisory committees in their development, use, and long-term sustainability. Strong school-community partnerships are essential to effective agricultural education programs, particularly in small, rural communities where programs serve as connections between the school and local industry. Advisory committees play a critical role in maintaining these relationships, yet many agricultural educators lack clear, accessible resources to guide this work. This project addressed that need by creating a comprehensive, practice-based guide established from research and professional experience.

This guide started from a review of literature on school-community partnerships, advisory committees, and agricultural education …

Sounding W. B. Yeats’S “Cuchulain Comforted”, David Sergeant

School of Law, Humanities and Social Sciences

No abstract provided.

What Keeps Teachers: A Systematic Review Of Induction And Early-Career Teacher Retention In Rural Schools, Bobbie Jean Mcdonough

Teacher Education, Educational Leadership & Policy ETDs

Teacher retention remains a persistent challenge in United States education, particularly in rural K–12 public schools. This systematic review synthesized empirical research on induction and early-career teacher retention in rural United States settings published between 2000 and 2025. Guided by a postpositivist framework and aligned with PRISMA 2020 standards, 56 studies met inclusion criteria following structured database searches and multi-stage screening. Findings across the included studies indicate that retention was most consistently associated with induction, mentoring, professional learning, responsive leadership, collegial relationships, and teachers’ integration into their school and community, with no single support appearing sufficient in isolation. Across research …

Visits Related To Alcohol, Substance Use, And Mental Health In New Mexico’S Emergency Departments: Social Determinants Of Health And Discharge Disposition, 2021-2024, Samuel L. Swift, Maya Stefanovic, Dylan Pell

Population Health Research and Scholarship

No abstract provided.

The Impact Of Social Emotional Learning On Chicanx Students And Their Educators, Alesia Renee Camacho

Chicana and Chicano Studies ETDs

My research on the impact of social emotional learning on Chicanx students and their educators aims to analyze how the planned implementation of a carefully curated curriculum centering on the students’ culture and lived experiences makes for a better overall experience. For this study, I use the interpretive paradigm as it allows me to explain how education can serve as a tool to illuminate the injustices that students and their families face in their lives and, in turn, how these injustices are addressed in Ethnic Studies courses. Chicana/o/x Studies scholars have long advocated for utilizing students’ knowledge, experiences, perspectives, and …

Portrait Shadow Removal Via Self-Exemplar Illumination Equalization, Qian Huang, Cheng Xu, Guiqing Li, Ziheng Wu, Shengxin Liu, Shengfeng He

Research Collection School Of Computing and Information Systems

We introduce the Self-Exemplar Illumination Equalization Network, designed specifically for effective portrait shadow removal. The core idea of our method is that partially shadowed portraits can find ideal exemplars within their non-shadowed facial regions. Rather than directly fusing two distinct classes of facial features, our approach utilizes non-shadowed regions as an illumination indicator to equalize the shadowed regions, generating deshadowed results without boundary-merging artifacts. Our network comprises cascaded Self-Exemplar Illumination Equalization Blocks (SExmBlock), each containing two modules: a self-exemplar feature matching module and a feature-level illumination rectification module. The former identifies and applies internal illumination exemplars to shadowed areas, producing …

Trace: Securing Smart Contract Repository Against Access Control Vulnerability, Chong Chen, Lingfeng Bao, David Lo, Yanlin Wang, Zhenyu Shan, Ting Chen, Guangqiang Yin, Jianxing Yu, Zibin Zheng, Jiachi Chen

Research Collection School Of Computing and Information Systems

Smart contract vulnerabilities have led to billions of dollars in economic losses. Among these, improper Access Control, which allows unauthorized users to execute restricted functions, is particularly prevalent and has caused significant financial damage. Smart contract repositories contain source code, documentation, configuration files, and other artifacts necessary for building and deploying smart contracts. GitHub hosts numerous open-source repositories of this kind, which serve as intermediate artifacts in development and require compilation and packaging to produce deployable contracts. Third-party developers often reference, reuse, or fork code from these repositories during custom development. However, if the referenced code contains vulnerabilities, it can …

Stacked From One: Multi-Scale Self-Injection For Context Window Extension, Wei Han, Pan Zhou, Shuicheng Yan

Research Collection School Of Computing and Information Systems

The limited context window of contemporary large language models (LLMs) remains a primary bottleneck for their broader application across diverse domains. Although continual pre-training on long-context data offers a straightforward solution, it incurs prohibitive data acquisition and computational costs. To address this challenge, we propose SHAREDLLM, a novel framework based on multi-grained context compression and query-aware information acquisition. SHAREDLLM comprises two stacked short-context LLMs: a lower model serving as a compressor and an upper model acting as a decoder. The lower model compresses long inputs into compact, multi-grained representations, which are then forwarded to the upper model for context-aware processing. …

Dreamcs: Geometry-Aware Text-To-3d Generation With Unpaired 3d Reward Supervision, Xiandong Zou, Ruihao Xia, Hongsong Wang, Pan Zhou

Research Collection School Of Computing and Information Systems

While text-to-3D generation has attracted growing interest, existing methods often struggle to produce 3D assets that align well with human preferences. Current preference alignment techniques for 3D content typically rely on hardly-collected preference-paired multi-view 2D images to train 2D reward models, when then guide 3D generation — leading to geometric artifacts, such as the Janus face problem and geometric incompleteness, due to their inherent 2D bias. To address these limitations, we construct 3D-MeshPref, the first large-scale unpaired 3D preference dataset, featuring diverse 3D meshes annotated by a large language model and refined by human evaluators. We then develop RewardCS, the …

Where Did It Go Wrong? Attributing Undesirable Llm Behaviors Via Representation Gradient Tracing, Zhe Li, Wei Zhao, Yige Li, Jun Sun

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have demonstrated remarkable capabilities, yet their deployment is frequently undermined by undesirable behaviors such as generating harmful content, factual inaccuracies, and societal biases. Diagnosing the root causes of these failures poses a critical challenge for AI safety. Existing attribution methods, particularly those based on parameter gradients, often fall short due to prohibitive noisy signals and computational complexity. In this work, we introduce a novel and efficient framework that diagnoses a range of undesirable LLM behaviors by analyzing representation and its gradients, which operates directly in the model's activation space to provide a semantically meaningful signal linking …

Propaganda Ai: An Analysis Of Semantic Divergence In Large Language Models, Nay Myat Min, Long H. Pham, Yige Li, Jun Sun

Research Collection School Of Computing and Information Systems

Large language models (LLMs) can exhibit concept-conditioned semantic divergence: common high-level cues (e.g., ideologies, public figures) elicit unusually uniform, stance-like responses that evade token-trigger audits. This behavior falls in a blind spot of current safety evaluations, yet carries major societal stakes, as such concept cues can steer content exposure at scale. We formalize this phenomenon and present RAVEN (Response Anomaly Vigilance), a black-box audit that flags cases where a model is simultaneously highly certain and atypical among peers by coupling semantic entropy over paraphrastic samples with cross-model disagreement. In a controlled LoRA fine-tuning study, we implant a concept-conditioned stance using …

Managing Reproducibility Debt In Scientific Software: A Practical Framework, Zara Hassan, Christoph Treude, Graham Williams, Michael Norrish, Alex Potanin

Research Collection School Of Computing and Information Systems

Scientific software includes end-user applications, modelling tools, research software for publications, and production systems for real users. It plays a key role across various scientific disciplines by enabling large-scale computation, simulation, and data analysis. Unlike commercial software, scientific software is often developed in dynamic research environments with limited engineering practices, documentation, or testing. This makes it fragile and difficult to reproduce results, even when code and data are available, conditions in which Reproducibility Debt (RpD) accumulates. This paper presents the Reproducibility Debt Management Framework (RpD-MF), which is grounded in evidence from a systematic literature review, practitioner interviews, and a global …

Llmqua: Practical Backdoor Injection On Large Language Model Quantization, Xiangxiang Chen, Peixin Zhang, Jun Sun, Jin Song Dong, Wenhai Wang, Jingyi Wang

Research Collection School Of Computing and Information Systems

Quantization is widely used to enable local deployment of large language models (LLMs) on resource-constrained devices. Recent work (e.g., QuRA) shows quantization can be exploited via rounding manipulation to implant backdoors. However, such an attack has been evaluated only on small models and does not directly apply to LLMs due to three key constraints: (1) limited poisoning data from small, task-agnostic calibration sets; (2) layer-wise quantization restricting adversarial access to global representations; and (3) lack of gradient access in quantization pipelines, blocking gradient-based attacks.We propose LLMQuA, a practical quantization-phase backdoor attack tailored to the LLM setting. LLMQuA (i) injects backdoors …

Prompting Frameworks For Large Language Models: A Survey, Xiaoxia Liu, Jingyi Wang, Jun Sun, Xiaohan Yuan, Guoliang Dong, Peng Di, Wenhai Wang, Dongxia Wang

Research Collection School Of Computing and Information Systems

Since the launch of ChatGPT, a powerful AI Chatbot developed by OpenAI, large language models (LLMs) have made significant advancements in both academia and industry, bringing about a fundamental engineering paradigm shift in many areas. While LLMs are powerful, it is also crucial to best use their power where “prompt” plays a core role. However, the booming LLMs themselves, including excellent APIs like ChatGPT, have several inherent limitations: (1) temporal lag of training data, and (2) the lack of physical capabilities to perform external actions. Recently, we have observed the trend of utilizing prompt-based tools to better utilize the power …

Teamwise: Exploring Virtually Embodied Ai Facilitation For Video-Based Team Onboarding, Venkata Akhila Rani Obilisetty, Mikkeline Elleby, Anthony Tang, April Yi Wang

Research Collection School Of Computing and Information Systems

AI-mediated facilitation has emerged as a scalable approach to supporting onboarding and coordination in newly formed remote teams, yet existing systems are predominantly text-based. To explore how video-based, virtually embodied AI facilitators shape team experiences, we present TeamWise, which joins video-based onboarding meetings as an on-screen avatar. TeamWise guides teams through a structured facilitation flow of low-stakes activities to foster rapport, mutual awareness, and shared identity. While the overall sequence of activities and facilitation goals is predefined, the facilitator’s turn-by-turn utterances are generated dynamically by an LLM in response to participant input. We conducted a formative study of TeamWise to …

Challenges In Synchronous And Remote Collaboration Around Visualization, Matthew Brehmer, Maxime Cordeil, Christophe Hurter, Takayuki Itoh, Wolfgang Büschel, Mahmood Jasim, Arnaud Prouzeau, David Saffo, Lyn Bartram, Sheelagh Carpendale, Chen Zhu-Tian, Andrew Cunningham, Anthony Tang, Samuel Huron, Masahiko Itoh, Arpit Joshi, Kiyoshi Kiyokawa, Hideaki Kuzuoka, Bongshin Lee, Guillermo Molina León

Research Collection School Of Computing and Information Systems

We characterize 16 challenges faced by those investigating and developing remote and synchronous collaborative experiences around visualization. Our work reflects the perspectives and prior research efforts of an international group of 29 experts from across human-computer interaction and visualization sub-communities. The challenges are anchored around five collaborative activities that exhibit a centrality of visualization and multimodal communication. These activities include exploratory data analysis, creative ideation, visualization-rich presentations, joint decision making grounded in data, and real-time data monitoring. The challenges also reflect the changing dynamics of these activities in the face of recent advances in extended reality (XR) and artificial intelligence …

Reasoning On Time-Series For Financial Technical Analysis, Kelvin J. L. Koa, Jan Chen, Yunshan Ma, Huanhuan Zheng, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

While Large Language Models have been used to produce interpretable stock forecasts, they mainly focus on analyzing textual reports but not historical price data, also known as Technical Analysis. This task is challenging as it switches between domains: the stock price inputs and outputs lie in the time-series domain, while the reasoning step should be in natural language. In this work, we introduce Verbal Technical Analysis (VTA), a novel framework that combine verbal and latent reasoning to produce stock time-series forecasts that are both accurate and interpretable. To reason over time-series, we convert stock price data into textual annotations and …

Visual Loop: Bridging The Cognitive Gap In Software Development Through Visual-Ai Collaboration, Luis Filipe Fernandes Gomes, Xin Zhou, David Lo, Rui Abreu

Research Collection School Of Computing and Information Systems

Software development remains predominantly text-centric, despite decades of evidence showing that developers think and communicate visually. While sketches and diagrams externalize developers’ mental models, they remain disconnected from source code and quickly become outdated. Recent advances in foundation models, capable of both code and visual reasoning, create an opportunity to unify these representations. In this vision paper, we introduce Visual Loop, a continuous visual development environment that keeps code and informal sketches in bidirectional synchronization. Our prototype connects a code editor with a tablet-based visualization workspace, allowing developers to explore, annotate, and modify systems through freehand sketches interpreted by multimodal …

Autobackdoor: Automating Backdoor Attacks Via Llm Agents, Yige Li, Zhe Li, Wei Zhao, Nay Myat Min, Hanxun Huang, Xingjun Ma, Jun Sun

Research Collection School Of Computing and Information Systems

Backdoor attacks pose a serious threat to the secure deployment of large language models (LLMs), enabling adversaries to implant hidden behaviors triggered by specific inputs. However, existing methods often rely on manually crafted triggers and static data pipelines, which are rigid, labor-intensive, and inadequate for systematically evaluating modern defense robustness. As AI agents become increasingly capable, there is a growing need for more rigorous, diverse, and scalable \textit{red-teaming frameworks} that can realistically simulate backdoor threats and assess model resilience under adversarial conditions. In this work, we introduce \textsc{AutoBackdoor}, a general framework for automating backdoor injection, encompassing trigger generation, poisoned data …

Preliminaries & Editor's Introduction: In The Work Of Tension, Dinah Tapia Roma

Akda: The Asian Journal of Literature, Culture, Performance

No abstract provided.

Literary Colonization And Locating Avenues Of Subversion In Bobby Flores-Villasis' Suite Bergamasque, Michael Aaron C. Gomez

Akda: The Asian Journal of Literature, Culture, Performance

This paper examines four short stories included in the collection titled Suite Bergamasque, written by multi-awarded Negrense playwright and fictionist Bobby Flores-Villasis. A materialist reading situates Villasis within the canon of Philippine literature in English and analyzes the way his stories formally render the class antagonisms of history through the interconnected narratives of Dumaguete City’s sugar elite. Finally, this paper also contends that the political imagination of Villasis’ work exhorts contemporary Dumaguete writers to critically examine inherited hagiographies in order to describe fully the conditions that have shaped the city into its contemporary formation, particularly the phenomena of gentrification …

Panitikan At Pakikibakang Pesante: Kasaysayan Ng Pakikibaka Para Sa Repormang Agraryo Sa Tatlong Nobela Ni Lazaro Francisco (Literature And Peasant Struggle: History Of Agrarian Reform Struggles In Three Novels Of Lazaro Francisco), Jester Gabriel De Leon

Akda: The Asian Journal of Literature, Culture, Performance

Binasa ng papel na ito ang tatlong nobela ng Pambansang Alagad ng Sining sa Panitikan na si Lazaro Francisco na Ama (1929), Maganda Pa ang Daigdig (1955), at Daluyong (1962), upang ipatampok ang kasaysayan ng pakikibaka repormang agraryo buhat sa iba pang mga tunggalian na binunga ng nagbabanggaang interes ng mga magbubukid at panginoong maylupa sa isang lipunang malapyudal sang-ayon sa pagsusuring Maoismo. Matapat na isiniwalat ng mga akda ni Francisco ang kalagayan ng magbubukid sa rurok ng malapyudal na pananamantala mula sa panahon ng pananakop ng Estado Unidos hanggang sa panunungkulan ng mga burukrata-kapitalista matapos ang Ikalawang Digmaang Pandaigdig. …

Ang Estados Unidos Sa Hiraya Ni Manong Frankie: Paglalapat Ng Tematikong Pagsusuri Sa Mga Nobela Ni F. Sionil Jose Sa Diwa Ng Araling Kabanwahan (The United States In Manong Frankie’S Mind: Araling Kabanwahan In The Thematic Analysis Of F. Sionil Jose’S Novels), Mark Joseph Pascua Santos

Akda: The Asian Journal of Literature, Culture, Performance

Abstrak

Ginamit ng pag-aaral ang tematikong pagsusuri upang isalansan ang mga datos mula sa 13 nobela ni F. Sionil Jose ukol sa Estados Unidos at ugnayang Pilipino-Amerikano. Isinagawa ang paspasang pagbasa sa mga nobela, itinala ang mga pahinang may banggit sa “Estados Unidos” at mga salitang kaugnay nito, isinaalang-alang ang konteksto ng bawat banggit, at pinalitaw ang mga temang umiinog dito. Para ito sa layuning makapag-ambag sa Araling Kabanwahan (pagsasa-Filipino ng Area Studies/International Studies), kung saan pinag-aaralan ang mga kabihasnan sa labas ng Pilipinas gamit ang wika-at-perspektibang Pilipino. Hinahangad ng pag-aaral na maitaguyod ang ibayong interseksyon sa pagitan ng Araling …

Han Kang On Time And Body, Clarissa V. Militante

Akda: The Asian Journal of Literature, Culture, Performance

Han Kang's novel Human Acts delves into the liminality of time-space, as memories about a historical event become a ritual of remembering for those who survived tragedy. Time is not only historical, but can also be foregrounded by bodies, both dead and surviving. The survivors do not merely recall the past but inhabit it, too, so that they will not forget. This in itself is an act of defiance and resistance.