Digital Commons Network^™

Architecting A Complex Adaptive System Model For Selecting Policies To Reduce Kidney Discard, Lirim Ashiku

Doctoral Dissertations

"The kidney allocation system is a complex, evolving system involving multiple heterogeneous agents. Each agent exhibits emergent behavior that may not fully align with the complex system goals. Therefore, there is a need for a transdisciplinary systems approach to visualize the interdependency among agents and understand the dominant patterns that shape the kidney allocation system.

First, this research presented an incremental hierarchical system engineering approach in identifying the agents’ needs and behaviors toward the complex systems’ goal of maximizing deceased donor kidney utilization and reducing kidney discard. The hierarchical systems approach linked with model-based system engineering aided in eliciting agents’ …

Accelerating Circular Economy Transition For A Sustainable Built Environment: A Systems-Based Framework, Radwa Walid Yassin Eissa

Doctoral Dissertations

"The Circular Economy (CE) has gained momentum as a transformative framework for steering the construction value chain towards greater sustainability. However, this transition requires shifts in production and consumption patterns, adoption of circular business models, and the replacement of linear practices. Despite growing interest, CE adoption in construction faces persistent challenges, including sectoral fragmentation, lack of integrated governance frameworks, and limited coordination among stakeholders. This dissertation aims to accelerate the CE transition in the built environment through a multi-scale, interdisciplinary approach spanning five modules: (1) Module 1 develops a construction value chain-structured portfolio of CE strategies and assesses their implementation; …

Assessment Of Simulation Software Used For Cubesat Gnc Verification And Validation By University Research Teams, Alexander Taiyo Newett

Masters Theses

As the growth in university satellite teams continues, along with the greater trend in the small satellite market, the need for a guidance, navigation, and control verification and validation pipeline suitable for these young and inexperienced teams becomes evident. Much of the mathematical theory and software implementation of GNC concepts are large hurdles for teams largely composed of undergraduate students.

Many software packages exist that can help these teams achieve GNC verification and validation. If the learning curves of these software packages can be overcome, new satellite teams have the opportunity to better build and test GNC algorithms that are …

Assessment And Comparison Of Selected Carbon Ablation Models In Hypersonic Free-Flight And Arc-Jet Conditions, Andrew Steven Heider

Masters Theses

Accurate prediction of ablative thermal protection system (TPS) performance is critical for hypersonic vehicle design. However, numerical prediction of ablation remains challenging because results are influenced by complex physics and the choice of surface chemistry model and assumptions made in material response calculations. The objective of this work is to evaluate several carbon ablation models and their implementation within modern computational fluid dynamics (CFD) codes. Numerical simulations were performed using NASA’s LAURA flow solver and the commercial CFD code ANSYS Fluent, which coupled Navier-Stokes with surface chemistry models describing carbon oxidation, nitridation, and sublimation reactions. Several reaction sets were considered, …

Optimal Slotting In Hybrid Warehousing For Industry 4.0, Teng Yang

Masters Theses

In the era of Industry 4.0, the warehouse management system (WMS) employed by many firms prescribes hybrid storage, i.e., products with high turnover, called fast movers, are kept in random storage for a short time duration before being shifted to a dedicated storage area, while products with low turnover, called slow movers, remain in random storage. From dedicated storage, the products are dispatched to the customer. The challenge for managers is selecting the slot in dedicated storage to assign to each product while demand data change because of fluctuating market conditions; this problem is referred to as slotting in the …

Validating A Low-Cost Radio Frequency Characterization Framework For Development-Grade Software-Defined Radios In Short-Duration Cubesat Missions, Thomas Wayne Francois

Masters Theses

Software-defined radios (SDRs) and CubeSat platforms have reduced the cost and complexity of space-based communication systems, enabling broader participation in satellite missions. While low-cost radio hardware is increasingly accessible, the ability to characterize and validate its performance remains constrained by the high cost and limited access to traditional RF test equipment. This disparity creates a challenge for small satellite development teams, which must characterize communication-system technical performance with limited access to laboratory-grade instrumentation.

This thesis presents a low-cost RF characterization framework for assessing key radio-frequency performance metrics using readily available hardware and measurement techniques. The approach integrates frequency translation, SDR-based …

Design For Extrusion-Based Additive Manufacturing: Generation Of Guidelines For Ceramics With Comparison To Thermoplastics, Hollis Hervey Waites

Masters Theses

"Design for Additive Manufacturing (DfAM) has made much progress for polymer material extrusion processes (MEX-P), like Fused Deposition Modeling (FDM), but very little progress for ceramic MEX processes (MEX-C) like Direct Ink Writing (DIW). This thesis leverages MEX-P design guidelines to create an initial set of design guidelines for DIW. FDM and DIW processes and material properties are compared, and the effect of these factors on the differences in rules is discussed. Five design guidelines are identified as applying to all MEX. For three of these, an exact limit for DIW of alumina is studied: minimum corner radius in the …

Transformer-Based Language Models For Bitcoin Market Prediction And Interpretation, Erich Gozebina

Masters Theses

"In the context of a Master's thesis in applied mathematics, this work investigates compact transformer-based language models as an instrument for Bitcoin-related predictions and decision support. The work connects three topics: the structure of the Bitcoin system and its data, the mathematical and algorithmic foundations of deep autoregressive transformers, and the design of practical training pipelines for financial applications. On this foundation, a reproducible ETL pipeline for Bitcoin data is developed and two forecasting experiments are conducted with the compact language model nanochat. The first experiment approaches the prediction of next-day price movements through autoregressive next-token generation based on structured …

Characterizing A Delay-Programmable Two-Color Femtosecond Light Source For Coherent Control Of Atomic Multi-Photon Ionization Processes, Mason Tanner Toombs

Masters Theses

"In this work a delay-programmable two-color femtosecond laser based on a chirped-seed noncollinear optical parametric amplifier was characterized. This design utilizes a titanium-sapphire crystal oscillator to generate broadband pulses of light spanning approximately 600-1200 nm, with a pulse duration of ~5 fs, repetition rate of 80 MHz, and pulse energy of ~2.5 nJ. An infrared portion of the light, spanning approximately 1020-1060 nm, is split off from the pulse and used to generate a pump beam. By dispersing the remaining seed beam and controlling the relative timing delay between the seed and the pump, tunable frequencies within the seed can …

Structured Decomposition And Efficient Adaptation For Scientific Data Movement: From Transfer Concurrency To Genomic Data Acquisition, Rasman Mubtasim Swargo

Masters Theses

"The end-to-end performance of scientific data movement is increasingly limited not by raw network capacity but by whichever resource along the path is momentarily slowest, a bottleneck that no single static configuration can track. This thesis argues that the right response is to decompose each problem along the resource or workflow axis where bottlenecks vary, adapt only the genuinely dynamic control variables at runtime, and make that adaptation efficient through utility-guided or offline-learned control rather than expensive online search. The thesis develops this principle through four systems of widening scope. AutoMDT decomposes a transfer by operation, assigning separate concurrency levels …

Bitcoin Halving: How Effective Is It In Driving Cryptocurrency Market Dynamics?, Nyoman Sri Subawa, Caren Angellina Mimaki, I. Made Oka Mahendra, Made Srinitha Millinia Utami

Research outputs 2022 to 2026

Bitcoin halving is a quadrennial event that halves mining rewards and is believed to influence cryptocurrency prices and cryptocurrency market dynamics. This study examines the effect of Bitcoin halving on Cryptocurrency Prices, with Government Regulations, Market Sentiment, and Cryptocurrency Performance as mediating variables. A quantitative research approach was employed, gathering original data via survey instruments from 294 participants within the cryptocurrency community in Bali, which were analyzed using PLS-SEM. The findings indicate that Bitcoin halving exerts a favorable and statistically meaningful influence on Government Regulations, Market Sentiment, Cryptocurrency Performance, and Cryptocurrency Prices. Market Sentiment fully mediates the influence of Government …

Resolving Heterogeneity In Lymph Node Stromal Cells Using High-Dimensional Analysis Of Non-Optimized Flow Cytometry Data, Mikala E Heon, Eduardo Rosa-Molinar

2020-Current year OA Pubs

Lymph Node Stromal Cells (LNSCs) are a diverse population of cells responsible for maintaining the lymph node environment and regulating the immune response. Given these roles, they have the potential to help replicate lymph node functions

Professional Development To Inspire, Support, And Extend Stem-Related Learning, Somayeh Ba Akhlagh, Asma Hulayyil Aljohani, Maryam Jamal Alharthi, Nahla Mahmoud Gahwaji, Nouf Mohammed Albadi, Marianne Knaus

Research outputs 2022 to 2026

The success of STEM education in early childhood education is reliant on the pedagogical practices of teachers. Effective teaching of STEM requires specific knowledge of the four disciplines of STEM, appropriate teaching and learning methods and relevant experiences. In Saudi Arabia the teaching of STEM is a relatively new field, and this paper outlines a research project to promote the teaching and learning of STEM through professional development workshops. The research is informed by Vygotsky’s cultural-historical/socio-cultural theory, acknowledging the crucial role of social interaction and cultural context in a collaborative learning environment. To evaluate the project, a mixed methods approach …

What Are Information Literacy Skills? Western Australian Primary Teachers’ Interpretations Of The Ict Curriculum, Louise Moroney, Vaille Dawson

Research outputs 2022 to 2026

Teachers must equip students to navigate an increasingly complex world of unique challenges and opportunities, necessitating the development of a diverse range of transferable skills. These skills are embedded in the General Capabilities (GC) of the Australian school curriculum. Upper primary school teachers’ interpretations of one of the GC, Information and Communication Technology (ICT) learning progressions, was examined, as these skills have become increasingly important with the rise in generative and assistive artificial intelligence. Using an interpretivist paradigm, an exploratory study was used to determine the areas where 36 teachers differed in their interpretations of the learning progression. Data collected …

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 …

Feeling Giggity: Ambiguous Emojis In Teaching And Learning Communications, Mary Kynn, Nicole Reinke, Eva Hatje

Research outputs 2022 to 2026

There is an increase in the number of digital platforms used in higher education classrooms that promote using emojis to capture students’ emotions. However, there is little evidence to suggest that interpretation of emojis is reliable in this context. This pilot project explored if emojis can reliably signify the emotions expressed by first-year university students. Students were asked to record their emotions by selecting a representative emoji and using free text to describe its meaning. A total of 72 responses were recorded in an anonymous online survey. Happy face emojis were used more frequently than emojis representing neutral or unpleasant …

Priority Questions For The Next Decade Of Blue Carbon Science, Peter I. Macreadie, George E. Biddulph, Pere Masque, Hilary Kennedy, Jimena Samper-Villarreal, J. Patrick Megonigal, Hannah K. Morrissette, Tania E. Romero-Gonzalez, Vanessa Hatje, Jana Friedrich, Sigit D. Sasmito, Kenta Watanabe, Inés Mazarrasa, Dorte Krause-Jensen, Janine B. Adams, Miguel Cifuentes-Jara, Ariane Arias-Ortiz, Andre S. Rovai, Milica Stankovic, Kirsten Isensee, Ana M. Queirós, Luzhen Chen, Jorge Herrera-Silveira, Catriona L. Hurd, Rashid Ismail, Ken W. Krauss, Anna Lafratta, Maria M. Palacios, William E.N. Austin

Research outputs 2022 to 2026

Blue carbon ecosystems, classically defined as mangroves, tidal marshes and seagrasses, but increasingly expanded to include ecosystems such as tidal flats, macroalgal forests and shelf sediments, contribute to climate change mitigation and biodiversity support. Here, seven years after the last global assessment of research priorities, we conducted a priority-setting exercise to identify persistent knowledge and implementation gaps, and the strategic priorities that must be addressed to enable scalable, high-integrity and equitable management of blue carbon ecosystems in a rapidly evolving policy and finance landscape. The highest priority focuses on managing blue carbon ecosystems to support coastal communities while integrating traditional …

Does Class Ability Grouping In Secondary Schools Improve Students’ Literacy Scores On Australia’S Naplan Tests?, Olivia Johnston, Christa Norris, Peter Palamara

Research outputs 2022 to 2026

Many schools choose to use ability grouping, despite longstanding evidence that it is inequitable and does not improve overall academic outcomes. One reason that the practice of grouping students by ‘ability’ continues is because of pressure to perform on standardised tests. Educators hold beliefs that grouping students for English classes, for example, will improve their literacy scores. This paper presents findings from a study about class ability grouping for English in Australia and how different class grouping practices relate with students’ achievement on Australia’s standardised literacy test. The findings draw on data from our Class Ability Grouping Survey, where participant …

Let’S Make The Change: Addressing The Knowledge Gaps And Building Confidence In Teaching Aboriginal Perspectives For Pre-Service Teachers, Sarah Booth, Libby Jackson-Barrett, Mary Anne Macdonald, Renae Isaacs-Guthridge, Sian Bennett

Research outputs 2022 to 2026

Teaching Aboriginal perspectives and Aboriginal students by non-Indigenous teachers can feel daunting; however, this need not be the case. This study focuses on two frameworks that can be used to motivate pre-service teachers to feel more confident in teaching Aboriginal perspectives even when starting with trepidation in this area. To explain further, this study explored the impact an Aboriginal Contexts in Education unit had on pre-service teachers’ readiness to teach Aboriginal students and Aboriginal curriculum. Through two frameworks pre-service teachers were exposed to a range of Aboriginal perspectives through Aboriginal educators, authors, and resources, and spoke of their appreciation of …

Measuring Teachers’ Beliefs In Their Capacity To Use Differentiated Instruction In Their Classrooms: Development, Validation And Confirmation Of A Self-Efficacy Scale, Kathryn Gibbs, Stuart Woodcock, Nicole Dargue, Leah Le, Eunjae Park, Tom Porter, Gemma Scarparolo

Research outputs 2022 to 2026

The purpose of this study was to develop, validate and confirm a scale to gain a better understanding of teachers’ beliefs in their capacity to use differentiated instruction in their classrooms. Differentiation is an effective approach to teaching, designed to enable equitable learning opportunities for every student. Teachers are recommended to differentiate aspects of teaching, instruction, learning, assessment and the learning environment due to the increasing student heterogeneity within classrooms worldwide. Emerging literature has suggested that teacher self-efficacy may influence how teachers use this teaching approach. It is unknown if there is an existing scale that measures teachers’ self-efficacy when …

Optimizing Subgroup Selection In Petrochemical Industries: A Robust Data Envelopment Analysis Approach For Uncertainty Management, Sadegh Niroomand, Hilda Saleh, Morteza Shafiee, Dragan Pamucar, Ali Mahmoodirad

Research outputs 2022 to 2026

This study addresses the critical challenge faced by organizations in selecting an optimal subgroup of decision-making units (DMUs). Such a selection procedure can significantly influence efficiency, profitability, and strategic development. Recognizing the limitations of existing methods in handling inexact data and incorporating managerial preferences, this study proposes a novel framework that integrates data envelopment analysis (DEA) with binary linear programming models. The model applies belief-degree–based representations of uncertainty to capture imprecise inputs and outputs. For this model, two solution approaches—namely, chance-constrained programming and expected value approaches—were developed. These approaches are suitable for real-world applications using standard optimization software. The effectiveness …

Attacks And Detections In Recommender Systems: A Comprehensive Analysis For Models, Progresses, And Trends, Yan Feng, Zhihai Yang, Kexin Li, Jianxin Li, Pinghui Wang, Zhiquan Liu

Research outputs 2022 to 2026

Recommender systems (RSs), as crucial components of online services, can help users efficiently obtain information they may like. In reality, RSs face long-term threats. Attackers manipulate recommendation results by injecting malicious data in order to obtain benefits. At present, research on the security of RSs lacks a comprehensive understanding of attack capabilities. Moreover, existing defense strategies have not yet been systematically associated with attack characteristics. More importantly, existing defense methods rarely focus on real unlabeled data in practical application scenarios for anomaly detection and forensics. Therefore, this survey systematically analyzes the security of RSs and provides new insights. Specifically, we …

A Comprehensive Review Of Cyber Security And Current Practices In Global Mining Critical Infrastructure, Abu Barkat Ullah, Wanli Ma, Mohiuddin Ahmed, Bazlur Rashid, Munir Ahmad Saeed, Omer Arshad, Utkarsh Raghav

Research outputs 2022 to 2026

The purpose of the study is to explore the reasons behind the low uptake of Information Security Management Standards (ISMS), Asset Management, and Business Continuity Plans despite increasing cyber threats to the mining sector. Mining companies need to modernize and automate to keep up with the ‘Fourth Industrial Revolution’, driven by disruptive technology, forcing systems and technologies to become more integrated, increasing cyber attack threats. To address this, we conducted a literature review analyzing the mining industry across various regions. The research is based on a qualitative analysis of diversified literature. The results highlighted factors behind the low uptake of …

Artificial Intelligence, Fundamental Motives, And Evolutionary Mismatch, Amy J. Lim, Jose. C. Yong, Edison Sora Tan

Research Collection School of Social Sciences

In recent years, the intersection of artificial intelligence (AI) and psychology has garnered unprecedented attention, particularly following the advent of generative AI tools in 2022. These tools, capable of producing human-like text, images, and even deepening our understanding of cognitive processes, have not only captured the public imagination but also sparked new concerns and debates within the psychological community. While AI has been a subject of research for decades, the emergence of its generative capabilities has truly thrust AI into the spotlight. This article explores how these advancements are reshaping our understanding of human cognition and behavior, as well as …

Enhancing Healthcare Security: Manifold-Aware Machine Learning For Robust Adversarial Attack Detection In Iomt Networks, Mohmmad Al-Fawa’Reh, Mohammed Kaosar

Research outputs 2022 to 2026

The widespread adoption of Internet of Medical Things (IoMT) devices and the increasing movement towards telehealth have revolutionized healthcare delivery but also introduced significant security challenges. Tiny Machine Learning (TinyML) models deployed on resource-constrained medical devices are vulnerable to adversarial attacks that can compromise patient data and device functionality, posing risks to patient safety. To address these critical security concerns, this paper proposes MARD (Manifold-Aware Robust Defense), a defense mechanism designed to enhance the robustness of TinyML models. MARD trains a compact student model by transferring knowledge from a teacher model that incorporates Graph-based Manifold Regularization (GMR) and Manifold Mixup …

Success Criteria: Sustainable Efficacy In Australian Farmer Groups, David K. Mckenzie, Janine Joyce, Kerstin K. Zander, Penelope A.S. Wurm, Kim M. Caudwell

Research outputs 2022 to 2026

Purpose: To examine the factors and processes that sustain the efficacy of farmer groups as extension intermediaries for influencing collective innovation, and knowledge co-creation and exchange. Design/Methodology/Approach: Data was collected from farmer interviews, focus groups, and the published digital documents of five farmer groups across SE Australia. A grounded theory mixed-methods approach was used for data collection and analysis, aided by Atlas software in constructing concepts and a concept map representing group processes. Findings: The ability of groups to influence farm innovation, and farmer learning and knowledge co-creation, depends on the group efficacy. Group identity in advancing farmer interests and …

Preparing For Long-Acting Technologies: A Multistate Analysis Of Prep Persistence And Hiv And Sti Lab Coverage Among Oral Prep Initiators In St. Louis, Missouri (2014-2021), Lindsey M Filiatreau, Rupa Patel, Kate Curoe, Ashley Underwood, Joseph Cherabie, Elvin H Geng, Aditi Ramakrishnan, Rachel Presti, Aaloke Mody

2020-Current year OA Pubs

BACKGROUND: Engagement in pre-exposure prophylaxis (PrEP) care and routine screening for HIV and sexually transmitted infections (STIs) is critical to realizing the full benefits of this HIV prevention strategy.

METHODS: We enrolled a cohort of individuals seeking PrEP services in two clinics in Missouri, an Ending the HIV Epidemic priority state, from June 2014 to November 2021. We used electronic health record and survey data to explore outcomes in the 2 years following linkage to care using multistate methods. We assessed transitions between eight mutually exclusive care states differentiated by receipt of a prescription, lab coverage status, and retention. We …

A Novel Hybrid Robust Transfer Learning-Based Adaptive Fractional-Order Super-Twisting Sliding Mode Controller Enhanced For Speed Regulation Of Brushless Dc Motor, Seyyed Morteza Ghamari, Asma Aziz, Daryoush Habibi

Research outputs 2022 to 2026

Brushless DC (BLDC) motors are widely used in applications that are highly-efficient, reliable, and compact, such as electric vehicles, robotics, and medical devices. However, the inherent nonlinearities and load sensitivity of BLDC motors require a robust and adaptive control strategy to ensure satisfactory performance under various operating conditions. Sliding mode control (SMC) has been widely used for the BLDC drives. However, because of its simplicity and robustness, the control effectiveness of the control is limited by the sensitivity to the disturbances and the chattering phenomenon. To remedy this, super-twisting (ST) technique has been proposed to achieve smoother response and better …

Beyond Assumptions: What Students Really Think About School Wellbeing Programs, Amanda Madden

Research outputs 2022 to 2026

The study examined students’ perceptions of effective components in school-based wellbeing programs, addressing a critical gap where adolescent voices are absent. Data was gathered through a questionnaire, individual interviews, and focus groups conducted with 36 Year 12 students across three independent co-educational schools in Western Australia. Thematic analysis identified seven key components essential for effective wellbeing programming: targeted content providing respite from academic pressures, engaging and relatable presenters, strategic timing, developmental appropriateness, meaningful measurement, genuine teacher engagement, and authentic incorporation of student voice. Students valued practical, non-academic content and expressed scepticisms about teacher-delivered programs. Timing emerged as a previously underexplored …

Reflecting On Themes From Telehealth Consultations Early In The Pandemic: An Opportunity To Learn From Multiprofessional Colleagues, Maggie Meeks, Laura R. Joyce, John Dean, Lorna Davies, Tika Ormond, Philippa Seaton, Dale Sheehan, Dean Sutherland, Melanie Welfare, Arindam Basu

Research outputs 2022 to 2026

Aims: This study is aimed at documenting the reflections of New Zealand healthcare professionals on the use of synchronous telehealth consultations. Methods: A qualitative narrative inquiry was conducted to explore the practice of telehealth in New Zealand. Purposive sampling was used to identify clinicians from multiple professions who used telehealth during the initial phase of the COVID-19 pandemic. Fifteen semistructured interviews were conducted between October 2020 and May 2021 with clinicians from primary and secondary care, including multiple professional backgrounds. Interview transcripts were analysed thematically. Results: Six themes were identified: (1) equitable access: There were concerns regarding equitable access to …