Digital Commons Network^™

Adaptive Boundary-Aware Fact-Checker Placement For Misinformation Suppression In Social Networks, Mostafa Taghizade Firouzjaee, Ghazal Naderi, Ross Gore, Neda Moghim

School of Cybersecurity Faculty Publications

The spread of fake news on online social networks is driven by imitation-based user behavior and network topology, often leading to persistent misinformation clusters and echo chambers. In this study, we develop a spatial evolutionary game-theoretic framework in which agents update their latent opinions through payoff-biased imitation, while external fact-checkers act as non-imitative intervention nodes. Building on this formulation, we propose an adaptive, boundary-aware intervention mechanism that dynamically regulates both the density and spatial allocation of fact-checkers according to real-time system conditions. Competing information clusters are identified through local neighborhood composition, enabling boundary nodes, i.e., interfaces between fake-news and non-fake-news …

The Classical Limit In Geometric Quantization By Group Extension, Paul Bracken

School of Mathematical & Statistical Sciences Faculty Publications

Physical systems as a rule are associated with a symmetry group. The group approach to geometric quantization makes use of this to introduce a quantization by means of group extension. This procedure is discussed and applied to a physical system whose group law has its origin with the Galilean group. The main intention is to investigate the classical limit and its relationship under this approach to geometric quantization. The classical quantization conditions are obtained based on a deeper foundation.

Efficient Search For Detection Candidates Using A Peak Finder Strategy For All-Sky-All-Frequency Gravitational Wave Radiometer, Arindam Sharma, Deepali Agarwal, Sanjit Mitra

Physics & Astronomy Faculty Publications

The first all-sky-all-frequency (ASAF) radiometer search was conducted using data from the first three observing runs of the Advanced LIGO and Advanced Virgo detectors. The significance of this search lies in its fast and unmodeled approach, leveraging a cross-correlation technique to identify common signals across the detector network. As a result, this method serves as an excellent alternative to search for unknown or poorly modeled continuous wave sources and narrow band components of the gravitational wave (GW) background. For continuous wave sources whose waveform can be modeled, this method can serve as the first stage of a hierarchical scheme by …

Computational Insights Into Orthotropic Fracture: Crack-Tip Fields In Strain-Limiting Materials Under Non-Uniform Loads, Saugata Ghosh, Dambaru Bhatta, S. M. Mallikarjunaiah

School of Mathematical & Statistical Sciences Faculty Publications

A finite element framework is presented for analyzing crack-tip phenomena in transversely isotropic, strain-limiting elastic materials. Mechanical response is characterized by an algebraically nonlinear constitutive model, relating stress to linearized strain. Non-physical strain singularities at the crack apex are mitigated, ensuring bounded strain magnitudes. This methodology significantly advances boundary value problem (BVP) formulation, especially for first-order approximate theories. For a transversely isotropic elastic solid with a crack, the governing equilibrium equation, derived from linear momentum balance and the nonlinear constitutive model, is reduced to a second-order, vector-valued, quasi-linear elliptic BVP. This BVP is solved using a robust numerical scheme combining …

The Ai Revolution In Virtual Try-Ons: A Means-End Chain Model Perspective, Ju-Young M. Kang, Ji Young Lee, Dooyoung Choi, Sumin Helen Koo, Jeehyun Song, Youngjin Bahng

Educational Leadership & Workforce Development Faculty Publications

Leading brands have begun to implement artificial intelligence-driven virtual try-on (AI VTO) technology, which helps reduce returns and increase conversion rates, repeat purchases, and customer loyalty. This research aimed to examine how retail user experience with specific perceived quality factors of AI VTOs influences users’ value equity and downstream loyalty and to investigate the moderating effects of clothing in relation to the self as structure and concern for physical appearance, based on a Means–End Chain model. Data were collected from 509 U.S. online apparel shoppers using a consumer panel. Structural equation modeling and multigroup analysis were used for data analysis. …

Design Of An Economic Order Quantity–Based Dashboard For Vaccine Packaging Inventory Management, Hadi Susanto, Susmitha Canny, Alexandra Elizabeth Callistha, Shakira Dwi Purwandari, Naila Davina Aurelia

ASEAN Journal on Science and Technology for Development

Background: Timely availability of vaccine packaging is critical to pharmaceutical supply chain reliability, as packaging materials play a key role in maintaining cold chain integrity during distribution. Inadequate availability of packaging materials can disrupt vaccine delivery even when finished vaccines are ready for shipment. The case company faces frequent delivery delays, insufficient safety stock, and irregular replenishment of vaccine packaging materials, which have jeopardized the organization’s target of achieving a 90% on-time delivery rate.

Objective: To design and evaluate an Economic Order Quantity (EOQ)–based inventory dashboard for vaccine packaging that standardizes ordering decisions and strengthens stock visibility in pharmaceutical distribution …

Integrated Seismic And Sequence Stratigraphic Analysis Of The Abu Madi Formation, Baltim Field, Nile Delta, Egypt, Nouran Mostafa Eissa, Mostafa Toni, Alhussein Adham Basheer, Amr Talaat, Amir Ismail

Trends in advanced sciences and technology

Despite the economic significance of the Messinian Abu Madi Formation as a primary gas reservoir target in the Nile Delta Basin, a high-resolution, field-scale integration of seismic sequence stratigraphy with quantitative petrophysical characterization remains lacking for the Baltim area. This study addresses this gap by presenting an integrated seismic sequence stratigraphic and petrophysical analysis of the Upper Miocene Abu Madi Formation within the prolific Baltim gas fields, offshore Nile Delta, Egypt. The objectives are to characterize its depositional architecture, delineate reservoir distribution, and assess hydrocarbon potential. The workflow synthesizes well log data from five key wells with a grid of …

Ecological And Evolutionary Divergence Of A Shared Sympatric Color Polymorphism In Paracirrhites Hawkfish, Samuel Greaves

Graduate Studies Theses and Dissertations 2026

Color polymorphism provides a tractable window into how selection, gene flow, and ecology interact to maintain phenotypic diversity and initiate divergence. I investigate the ecological and genomic basis of sympatric light and melanistic morphs in two reef hawkfishes, Paracirrhites arcatus and P. hemistictus, across Guam and Hawai‘i. This study aims to determine whether the color morphs of these hawkfishes are a stable polymorphism or have begun the process of ecological speciation. For P. arcatus revealed substantially lower density on Guam (0.086 ind/m²) than reported for Hawai‘i (0.292 ind/m²) and a strong skew away from the melanistic morph on Guam …

First-Principles Insights Into Electronic And Magnetic Structure At Hybrid Interfaces And Low-Dimensional Materials And Reaction On Surfaces, Bushra Ashraf

Graduate Studies Theses and Dissertations 2026

Low-dimensional materials and transition metal surfaces/interfaces provide complementary platforms for understanding how dimensionality, symmetry, spin–orbit coupling (SOC), and interfacial charge transfer/hybridization jointly control electronic structure, emergent magnetism, and surface reactivity. Using first-principles modeling with experimental comparisons, this work aims to establish interfacial structure–property relationships across low-dimensional systems.

Strained Pd adlayers on 2H-MoS₂(0001) provide a controlled platform to separate strain-driven exchange from interface-induced quenching in an itinerant d-electron metal. Although expansive strain promotes magnetism in free-standing Pd, strong Pd–MoS₂ hybridization and charge transfer suppress the monolayer moment and leave a narrow thickness window where magnetism re-emerges in …

An Integrated Framework For Last-Mile Delivery Optimization Using Reinforcement Learning And Social Media-Based Traffic Prediction In Underdeveloped Megacities, Vasanth Bhat

Graduate Studies Theses and Dissertations 2026

Supply chain management has become increasingly critical as transportation costs rise and urban delivery systems place additional pressure on already congested networks. Last-mile delivery—the movement of goods from distribution centers to end users—represents the most expensive and operationally complex segment of the logistics process, particularly in underdeveloped megacities characterized by unpredictable traffic, limited infrastructure, and sparse real-time data. This dissertation proposes an integrated framework for optimizing last-mile delivery in such environments by combining social media–based traffic intelligence, machine learning, and deep reinforcement learning. The framework leverages unstructured, real-time data from social media platforms to enhance traffic prediction and incorporates these …

Learning-Based Optimization For Collaborative Truck-Drone Routing And Scheduling, Ahmad A. Bany Abdelnabi

Graduate Studies Theses and Dissertations 2026

Modern delivery networks increasingly rely on innovative technologies such as drones working alongside trucks to meet rising demands for fast and efficient last–mile transportation. Hybrid truck–drone delivery offers strong potential, but its effectiveness depends on careful synchronization between trucks and drones. Although drones provide fast, direct travel, their limited endurance and the need to coordinate launch and recovery with trucks create tightly coupled routing and scheduling interactions. Poor dispatch decisions can cause truck waiting, reduce parallelism, and increase mission completion time. These challenges motivate decision frameworks that explicitly model synchronization and develop scalable methods for coordinated truck–drone operations. This dissertation …

Advances In Active And Passive Integrated Photonic Devices On Thin-Film Lithium Niobate, Pooja S. Kulkarni

Graduate Studies Theses and Dissertations 2026

Thin-film lithium niobate (TFLN) has emerged as a powerful platform for integrated photonics, combining the exceptional electro-optic, nonlinear, and optical properties of bulk lithium niobate with the scalability and compactness of planar nanophotonic technologies. Building on these principles, advanced device architectures such as adiabatic dichroic filters have demonstrated exceptional spectral performance spanning over two octaves of bandwidth on the TFLN platform. Beyond reciprocal devices, it also offers promising pathways toward integrated nonreciprocal components. By leveraging broadband filtering structures and advanced nonlinear photonic design strategies, compact and monolithic optical isolators can be envisioned without relying on traditional magneto-optic materials. In the …

Study Of Fire Regimes In Southwestern Australia Using Geospatial Techniques, Ana Do Carmo Carvalho

Theses: Doctorates and Masters

The Northern Jarrah Forest in Southwestern Australia (SWA), part of a global biodiversity hotspot, is home to fire-sensitive tree species such as marri (Corymbia calophylla) and jarrah (Eucalyptus marginata). As climate change intensifies drought and extreme fire events, understanding the drivers of fire severity is increasingly critical. This thesis analyses fire regimes within the Mundaring drinking water catchment to better understand the spatiotemporal complexity of fire severity in relation to fire history and environmental factors.

The thesis commences with a review of three Fire History Databases (FHDs) used in SWA, highlighting significant inconsistencies and data gaps across time and space. …

An Investigation Into The Mechanisms, Barriers, Degree And Sphere Of Risk Influence In Corporate Security, Nicola Lockhart

Theses: Doctorates and Masters

This study investigates the sphere of corporate security risk influence within organisations, addressing the conceptual and practical ambiguity surrounding the activity’s capacity to shape organisational decisions, behaviours, and risk priorities. While corporate security’s protective role is widely recognised, its broader organisational risk influence remains under-theorised. The study defines the sphere of risk influence as the range of organisational stakeholders and environments with which the corporate security activity interacts, and within which it may engage, persuade, and mobilise action. This sphere is analytically constituted through the intersection of three dimensions: the mechanisms through which influence is attempted, the barriers that constrain …

Artificial Intelligence And Consumer Well-Being: A Cross Domain Systemic Review, Setar Lytle, Mahesh Gopinath

Marketing Faculty Publications

Artificial intelligence (AI) is increasingly embedded in everyday consumption, yet evidence on its longer-term implications for consumer eudaimonic well-being remains dispersed across disciplines and application contexts. This review integrates that literature to clarify the domains, theoretical explanations, and conditions through which AI shapes consumer well-being. Following PRISMA and SPAR-4-SLR procedures, we reviewed research published from January 2010 to January 2026. From 6058 records, 480 studies across psychology, business, and human-technology interaction met the inclusion criteria. The evidence is organised through psychological, social, and technological perspectives and identifies six interconnected domains: mental health, cognitive development, physical health, personal growth, autonomy and …

Rrto: A High-Performance Transparent Offloading System For Model Inference In Mobile Edge Computing, Zekai Sun, Xiuxian Guan, Zheng Lin, Yuhao Qing, Haoze Song, Zihan Fang, Zhe Chen, Fangming Liu, Heming Cui, Wei Ni, Jun Luo

Research outputs 2022 to 2026

Deploying Machine Learning (ML) applications on resource-constrained mobile devices remains challenging due to limited computational resources and poor platform compatibility. While Mobile Edge Computing (MEC) offers an offloading-based inference paradigm using GPU servers, existing approaches can be divided into non-transparent and transparent methods, with the former necessitating source-code modifications. Non-transparent offloading achieves high performance but requires intrusive code changes, limiting compatibility with diverse applications. Transparent offloading, in contrast, offers wide compatibility but introduces two challenges: performance degradation under MEC's low and fluctuating bandwidth, where per-operator remote procedure calls (RPCs) inflate end-to-end latency and energy consumption; and black-box logic reconstruction, which …

The Effects Of Financing Green And Brown Sectors: What Do Theories And Evidence Say?, Hao Liang, Maria Teresa Punzi

Research Collection Lee Kong Chian School Of Business

This paper critically examines the economic and welfare implications of financing green and brown sectors. Drawing on a comprehensive review of recent theoretical and empirical literature, we highlight that while conventional green finance—allocating capital toward environmentally friendly (“green”) sectors and away from carbon-intensive (“brown”) sectors—can promote decarbonization, it may also produce unintended externalities. In particular, it can inadvertently incentivize higher emissions from brown firms and contribute to economic disruption. Using a dynamic stochastic general equilibrium (DSGE) model, we demonstrate that lowering the cost of capital for green sectors leads to only modest reductions in emissions, whereas raising it for brown …

Understanding Climate Change And Wellbeing Through Bhutan's Pursuit Of Gross National Happiness, Tashi Dorji

Theses: Doctorates and Masters

Climate change has evolved into one of the biggest global challenges of the twenty first century reshaping ecological systems and social conditions with wide-ranging implications for human wellbeing. Bhutan offers a distinct context to explore interactions between climate change and wellbeing as it remains guided by its wellbeing-centred development philosophy of Gross National Happiness (GNH). At the same time, it remains highly vulnerable to climate change despite being the only carbon negative country in the world. Nonetheless, the intersections between climate change and GNH have not been systematically explored.

This research aims to explore the relationship between climate change and …

Computational And Ai Frameworks For Identifying Key Regulatory Genes And Their Target Genes In Plants And Humans, Md Khairul Islam

Dissertations, Master's Theses and Master's Reports

This dissertation presents computational and AI-driven frameworks for identifying key regulatory genes and their downstream targets across plant and human biological systems. Three studies address distinct challenges in genomic regulation using advanced machine learning and bioinformatics approaches.

The first study introduces DyGAF (Dynamic Gene Attention Focus), a dual-attention transformer framework that identifies and ranks disease-relevant biomarker genes by simultaneously modeling independent molecular responses and interdependent regulatory network behavior. Two attention models provide complementary perspectives on gene importance and are fused through a novel combination metric. Applied to COVID-19 nasopharyngeal swab profiles, the attention-weighted representations achieved 94.23% classification accuracy, high sensitivity, …

Memoryart: Enhancing Llms Via Multi-Memory Models With Adaptive Resonance Theory For Healthcare Agents, Renke Dai, Hebin Hu, Jiahui Zhang, Yilin Kang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Though promising in healthcare consultation applications, large language models (LLMs) face critical limitations in retaining and utilizing long-term memory across multiturn interactions. In particular, existing memory enhancing paradigms are constrained by limited context windows and embedding-based retrieval, often failing to maintain task relevance and still suffering from memory prototype collapse in multi-turn healthcare consultation. To address these challenges, we propose a cognitively-inspired memory framework named MemoryART, which is grounded in Adaptive Resonance Theory (ART)—a cognitive and learning theory of how humans and animals adapt to dynamic environments. MemoryART employs three memory modules—working memory, episodic memory, and semantic memory to support …

Paid Search Marketing Vs. Search Engine Optimization: Analytical Models Of Search Marketing Based On Search Engine Quality, Kai Li, Chunyang Shen, Mei Lin, Zhangxi Lin

Research Collection School Of Computing and Information Systems

As search engines are leading revenue growth in online marketing, search marketing has become a popular area of academic research. Although search engine advertising has interested researchers for decades and much has been learned, one thing that puzzles scholars is why search engine optimization companies are tolerated rather than excluded from the market, even though they capture a significant share of the advertising market. In this paper, we shed light on this phenomenon and establish an analytical model based on organic search quality. Through analysis of the model, we were able to draw several intriguing conclusions. First, there is no …

Design Principles For Customer-Engaging Digital Service Systems: An Action Research Study, Keng Leng Siau, Xiaofeng Chen, Xin Tan

Research Collection School Of Computing and Information Systems

Digital services represent a business approach employed by organizations to operate in the digital environment. However, systematic development guidelines for developing quality digital service systems are lacking in the literature. The authors identified four general challenges for developing and implementing customer-engaging digital service systems (CEDSS). By employing the method of canonical action research in a digital service system project, they derived 10 design principles for developing high-quality CEDSS. They empirically evaluated the design principles in the development project and through follow-up focus group sessions. The design principles provide applicable and actionable guidelines for the development of CEDSS.

Hybrid Learning And Optimization Methods For Solving Capacitated Vehicle Routing Problem, Monit Sharma, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We propose a hybrid quantum–classical framework for the Capacitated Vehicle Routing Problem (CVRP) that integrates the Augmented Lagrangian Method (ALM) with deep reinforcement learning (RL). Directly solving CVRP via Variational Quantum Eigensolver (VQE) requires a slack-based QUBO formulation, where converting inequalities to equalities greatly increases the qubit count. To circumvent this, we employ an ALM-based reformulation that enforces constraints through Lagrange terms instead of slack variables, drastically reducing quantum resource demands. An RL agent, trained with Soft Actor–Critic, adaptively tunes the Lagrange penalties to improve convergence and feasibility. Experiments show that RL-Q-ALM outperforms static-penalty and plain VQE baselines in both …

Instance Generation For Meta-Black-Box Optimization Through Latent Space Reverse Engineering, Chen Wang, Yue-Jiao Gong, Zhiguang Cao, Zeyuan Ma

Research Collection School Of Computing and Information Systems

To relieve intensive human-expertise required to design optimization algorithms, recent Meta-Black-Box Optimization (MetaBBO) researches leverage generalization strength of meta-learning to train neural network-based algorithm design policies over a predefined training problem set, which automates the adaptability of the low-level optimizers on unseen problem instances. Currently, a common training problem set choice in existing MetaBBOs is well-known benchmark suites CoCo-BBOB. Although such choice facilitates the MetaBBO's development, problem instances in CoCo-BBOB are more or less limited in diversity, raising the risk of overfitting of MetaBBOs, which might further results in poor generalization. In this paper, we propose an instance generation approach, …

(R2151) Error Estimates Of Barycentric Lagrange Interpolation, Alvira Yawar, Swarnima Bahadur

Applications and Applied Mathematics: An International Journal (AAM)

Barycentric interpolation, which comes from Lagrange interpolation, is a useful method in numerical analysis. In this research paper, we explain how the barycentric interpolation formula is derived and discuss its features. We compare its stability and performance with the traditional Lagrange formula. First, we show how to get the barycentric formula from the Lagrange polynomial and present it as a rational function. We also provide an estimate of the error. Then, we use numerical examples to show that the barycentric formula is more stable and works better, especially when the degree of interpolation is high. Our results show that the …

Exploring The Metric Dimension Of The Graph Representing A Four-Ring Polycyclic Aromatic Hydrocarbon: Interstellar 1-Cyanopyrene, Andrei Matthew V. Robino, Sebastian Alex C. Traviña, Karl Benedict P. Narag, Mark Anthony B. Casao, Helix Raven C. Llanes, Azriel C. Alejo, Jonel C. Celamor

Sinaya: A Philippine Journal for Senior High School Teachers and Students

A graph's metric dimension is a parameter that denotes the minimum possible number of vertices in a subset that gives each vertex in the graph a unique representation. Despite extensive research on the metric dimension of polycyclic aromatic hydrocarbons (PAHs), there is currently no focused analysis on the metric basis and metric dimension of 1-cyanopyrene. In chemistry, graphs can be used to depict molecular structures. In this study, graph theory, specifically the concept of metric dimensions, is applied to the molecular structure of 1-cyanopyrene, which was detected in space for the first time in 2024. 1-cyanopyrene is a molecule made …

Environmental Science And Sustainable Development: Behavioral Transformation To Knowledge System Integration For Sustainability Action, Ahyahudin Sodri, Herdis Herdiansyah

Journal of Environmental Science and Sustainable Development

Sustainability issues are now a global concern. However, knowing the root causes of problems and the target is not the only factor that constantly motivates change for the better (Wamsle & Osberg, 2022) as such change also requires encouragement from actors, including individuals, organizations, and communities. Therefore, the human aspect is crucial for the successful achievement of sustainability (Hariram et al., 2023). In other words, questions on sustainability are not just about "what should be done?" and also on “how to get people to do it?” and “why are currently available interventions not yet fully utilized?” …

Effect Of Real Quest Outdoor Learning On High School Students Climate Literacy, Siti Aisah, Abdul Hakim, Puardmi Damayanti

Jurnal Pendidikan Sains

This study investigates the influence of the Real Quest Outdoor Learning (ReQOL) model, which encompasses knowledge, attitudes, and behavior, on the climate literacy of high school students. A quasi-experimental design was performed with a non-equivalent control group; thus, a sample consisting of an experimental class (n = 34) and a control class (n = 32) was used. A one-way ANOVA test was used to test the differences between pretest and post-test scores at a 0.05 significance level. The basic knowledge on climate in the experimental group increased significantly (sig < 0.001), while the change in attitudes and behaviors was insignificant (sig = 0.339 and sig = 0.447, respectively). The fact that attitude and behavior did not improve significantly during the experiment can be justified by the existing Adiwiyata programme in schools. These findings indicate that the ReQOL model is a good way to help students understand climate issues better. Adding discovery-based outdoor learning to science classes has the potential to make students more aware of environmental issues and lay the groundwork for the development of responsible behavior. This underscores the scientific contribution and educational importance of the development of climate literacy within the curriculum.

Journal Of Roleplaying Studies And Steam (Jrpssteam) Vol. 4 [2025], Número 2 (Issue 2), Cristo Leon, Romano Ponce-Díaz Phd, Ivan Avila Gonzalez Phd, James Lipuma Dr., Bruce G. Bukiet, Ricardo Victoria-Uribe, Nazario Robles-Bastida, Chris Birmingham, Ximena Diaz Santillan, Edgar Francisco Vázquez Martínez He, Jorge Prieto Terrones, Juan Carlos C. González Vidal S, Edgar Meritano, Laura Magela Garcés Ramírez

Journal of Roleplaying Studies and STEAM

En una sesión de juego por medio del registro lingüístico se organiza la escena, se orienta la manera de nombrar las tareas, se distribuyen los roles actanciales, se establecen la expectativas; por lo tanto, se establece una puesta en escena. De tal forma, las prácticas lúdicas y ficcionales se configuran a partir de nuestra mirada del mundo e irremediablemente también reconfiguran esa misma mirada. El ser y el estar en un espacio es la especificidad mediática fundamental de los juegos de rol; dicho de otra manera, en los sistemas de juego de rol dentro de sus universos narrativos, en su …

Fructure Mechanisms And Fracture Distribution Patterns Of Main Roofs In Goaves Within Abandoned Mines, Tao Xuefeng, Shi Biming, Hua Xinzhu, Lin Baiquan, Yue Jiwei, Liang Yuehui, Zhang Chengcheng, Qin Hao, Yang Yong, Xue Yonglin

Coal Geology & Exploration

Objective In abandoned mines, the storage zones of free gas are closely associated with overburden fractures in goaves. To accurately estimate free gas resources in abandoned mines, it is necessary to thoroughly investigate the rupture mechanisms of blocks in main roofs in goaves, as well as the overburden fractures and rupture trace morphologies in goaves. Methods Based on the masonry beam theory, this study established a mechanical model for the primary cantilever beam of a main roof. The analytical solutions of the stress components in the primary cantilever beam were analyzed using the stress inverse method, and the mathematical expression …