Physical Sciences and Mathematics Commons^™

Expanding Australia's Defence Capabilities For Technological Asymmetric Advantage In Information, Cyber And Space In The Context Of Accelerating Regional Military Modernisation: A Systemic Design Approach, Pi-Shen Seet, Anton Klarin, Janice Jones, Michael N. Johnstone, Violetta Wilk, Stephanie Meek, Summer O'Brien

Research outputs 2022 to 2026

Introduction. The aim of the project was to conduct a systemic design study to evaluate Australia'sopportunities and barriers for achieving a technological advantage in light of regional military technological advancement. It focussed on the three domains of (1) cybersecurity technology, (2) information technology, and (3) space technology.

Research process. Employing a systemic design approach, the study first leveraged scientometric analysis, utilising informetric mapping software (VOSviewer) to evaluate emerging trends and their implications on defence capabilities. This approach facilitated a broader understanding of the interdisciplinary nature of defence technologies, identifying key areas for further exploration. The subsequent survey study, engaging 828 …

From Grain To Malt: Tracking Changes Of Ultra-Low-Gluten Barley Storage Proteins After Malting, Mahya Bahmani, Angéla Juhász, Utpal Bos, Mitchell G. Nye-Wood, Malcolm Blundell, Crispin A. Howitt, Michelle L. Colgrave

Research outputs 2022 to 2026

Barley (Hordeum vulgare L.) is a major cereal crop produced globally. Hordeins, the major storage proteins in barley, can trigger immune responses leading to celiac disease or symptoms associated with food allergy. Here, proteomics approaches were employed to investigate the proteome level changes of grain and malt from the malting barley cultivar, Sloop, and single-, double- and triple hordein-reduced lines. The triple hordein-reduced line is an ultra-low gluten barley cultivar, Kebari®. Using discovery proteomics, 2,688 and 3,034 proteins in the barley and malt samples were detected respectively. Through the application of targeted proteomics, a significant reduction in the quantity …

Unifying Context With Labeled Property Graph: A Pipeline-Based System For Comprehensive Text Representation In Nlp, Ali Hur, Naeem Janjua, Mohiuddin Ahmed

Research outputs 2022 to 2026

Extracting valuable insights from vast amounts of unstructured digital text presents significant challenges across diverse domains. This research addresses this challenge by proposing a novel pipeline-based system that generates domain-agnostic and task-agnostic text representations. The proposed approach leverages labeled property graphs (LPG) to encode contextual information, facilitating the integration of diverse linguistic elements into a unified representation. The proposed system enables efficient graph-based querying and manipulation by addressing the crucial aspect of comprehensive context modeling and fine-grained semantics. The effectiveness of the proposed system is demonstrated through the implementation of NLP components that operate on LPG-based representations. Additionally, the proposed …

Transient Diode Laser Absorption Spectroscopy For Measuring Collisional Quenching Rates Of Co And Its Potential For Studying H2o, Jordan M. Polvere

Master’s Theses

Motivated by the necessity of non-LTE models that account for species that are not in Local Thermodynamic Equilibrium (LTE) in Titan’s and Earth’s atmospheres, collisional quenching rates of CO and H2O_(g) have been studied. Providing more accurate and precise values of collisional quenching rate coefficients is crucial in the development of more advanced atmospheric models, which are important to fields of science such as meteorology and astronomy. Rates of collisional quenching of CO(v=1,2) by CO and CO(v=2) by N₂ at approximately 301-321 K were measured by transient diode laser absorption spectroscopy. The rate coefficients of CO(v=1)-CO, CO(v=2)-CO, and …

Types Of Teacher-Ai Collaboration In K-12 Classroom Instruction: Chinese Teachers' Perspective, Jinhee Kim

STEMPS Faculty Publications

The advancing power and capabilities of artificial intelligence (AI) have expanded the roles of AI in education and have created the possibility for teachers to collaborate with AI in classroom instruction. However, the potential types of teacher-AI collaboration (TAC) in classroom instruction and the benefits and challenges of implementing TAC are still elusive. This study, therefore, aimed to explore different types of TAC and the potential benefits and obstacles of TAC through Focus Group Interviews with 30 Chinese teachers. The study found that teachers anticipated six types of TAC, which are thematized as One Teach, One Observe; One Teach, One …

The Role Of Shopping Orientations And Intrinsic Experiential Value In Consumer's Willingness To Follow Embodied-Ai's Advice In Fashion Shoe Stores, Christina Soyoung Song, Ji Young Lee, Dooyoung Choi

STEMPS Faculty Publications

This study employs a synthesis of Intrinsic Motivation Theory with three shopping orientations, namely “adventure,” “idea,” and “personalized” shopping, in order to examine their potential influence on individuals' motivation towards shopping. We proposed that consumers’ experiential value of intrinsic enjoyment is an indispensable mediator that affects their willingness to follow EAI’s advice. The study offers novel insights into the way that consumers’ characteristics of influencing others’ clothing consumption affect their shopping motivations to find adventure and stimulation, keep up with new fashion trends and products information, and their preference to patronize stores and interact with store staff on a personal …

Ai-Designed Clothing And Perceived Values: What Can Move Consumers' Minds With The Ai-Designed Clothing?, Choi Dooyoung, Ha Kyung Lee

STEMPS Faculty Publications

This study investigates the perceived values of AI-designed clothing (quality, emotion, ease) and their impact on willingness to pay (WTP) and word-of-mouth (WOM), with the moderating effect of gender differences. A total of 314 respondents completed the survey via MTurk. Participants watched a video clip demonstrating how an AI system creates various clothing designs by altering garment elements (e.g., style, size). After watching the video clip, they were asked to answer a series of questions about the AI-designed clothing and themselves. The collected data were analyzed using AMOS 26.0. Results showed that, for male and female consumers, the quality value …

Higher Education Faculty Perceptions Of Chatgpt And The Influencing Factors: A Sentiment Analysis Of X, Yoseph Mamo, Helen Crompton, Diane Burke, Christine E. Nickel

STEMPS Faculty Publications

ChatGPT, an AI chatbot developed by OpenAI, was released in November 2022, sparking a significant surge in global awareness and utilization of generative AI across various domains. Although recent studies have acknowledged the significance of ChatGPT in the education sector, they have yet to focus on exploring faculty attitudes toward ChatGPT. We gathered a comprehensive corpus of tweets containing “#ChatGPT” and “#highered” between November 30th, 2022, and April 30th, 2023. We analyzed data by triangulating VADER, NRC lexicon, and ground coding. Findings suggest that 40% of the expressed sentiments were positive, 51% were neutral, and 9% were negative. The study …

Differences In Student-Ai Interaction Process On A Drawing Task: Focusing On Students' Attitude Towards Ai And The Level Of Drawing Skills, Jinhee Kim, Yoonhee Ham, Sang-Soog Lee

STEMPS Faculty Publications

Recent advances and applications of artificial intelligence (AI) have increased the opportunities for students to interact with AI in their learning tasks. Although various fields of scholarly research have investigated human-AI collaboration, the underlying processes of how students collaborate with AI in a student-AI teaming scenario have been scarcely investigated. To develop effective AI applications in education, it is necessary to understand differences in the student-AI interaction (SAI) process depending on students' characteristics. The present study attempts to fill this gap by exploring the differences in the SAI process amongst students with varying drawing proficiencies and attitudes towards AI in …

Permafrost Carbon: Progress On Understanding Stocks And Fluxes Across Northern Terrestrial Ecosystems, Claire C. Treat, Anna-Maria Virkkala, Eleanor Burke, Lori Bruhwiler, Abhishek Chatterjee, Joshua B. Fisher, Josh Hashemi, Frans-Jan W. Parmentier, Brendan M. Rogers, Sebastian Westermann, Jennifer D. Watts, Elena Blanc-Betes, Matthias Fuchs, Stefan Kruse, Avni Malhotra, Kimberley Miner, Jens Strauss, Amanda Armstrong, Howard E. Epstein, Bradley Gay, Mathias Goeckede, Aram Kalhori, Dan Kou, Charles E. Miller, Susan M. Natali, Youmi Oh, Sarah Shakil, Oliver Sonnentag, Ruth K. Varner, Scott Zolkos, Edward A.G. Schuur, Gustaf Hugelius

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Significant progress in permafrost carbon science made over the past decades include the identification of vast permafrost carbon stocks, the development of new pan-Arctic permafrost maps, an increase in terrestrial measurement sites for CO₂ and methane fluxes, and important factors affecting carbon cycling, including vegetation changes, periods of soil freezing and thawing, wildfire, and other disturbance events. Process-based modeling studies now include key elements of permafrost carbon cycling and advances in statistical modeling and inverse modeling enhance understanding of permafrost region C budgets. By combining existing data syntheses and model outputs, the permafrost region is likely a wetland methane …

Multiscale Modelling Of Brain Networks And The Analysis Of Dynamic Processes In Neurodegenerative Disorders, Hina Shaheen

Theses and Dissertations (Comprehensive)

The complex nature of the human brain, with its intricate organic structure and multiscale spatio-temporal characteristics ranging from synapses to the entire brain, presents a major obstacle in brain modelling. Capturing this complexity poses a significant challenge for researchers. The complex interplay of coupled multiphysics and biochemical activities within this intricate system shapes the brain's capacity, functioning within a structure-function relationship that necessitates a specific mathematical framework. Advanced mathematical modelling approaches that incorporate the coupling of brain networks and the analysis of dynamic processes are essential for advancing therapeutic strategies aimed at treating neurodegenerative diseases (NDDs), which afflict millions of …

The Atiyah-Hitchin-Singer Theorem And An 8-Dimensional Generalization, Timothy Ponepal

Theses and Dissertations (Comprehensive)

The Atiyah-Hitchin-Singer theorem states that the twistor almost complex structure on a certain S² bundle over an oriented Riemannian 4-manifold (M, g) is integrable if and only if the Weyl curvature tensor of g is self-dual. These ideas were developed by Roger Penrose connecting 4-dimensional Riemannian geometry with complex geometry. We present a new approach to the Atiyah-Hitchin-Singer theorem using horizontal lifts and their respective flows, cross products and the quaternions to show that the Nijenhuis tensor vanishes if and only if the Weyl curvature tensor of g is anti-self-dual. An eight dimensional generalization is presented when the …

Investigating The Mobility Of Arsenic In Subarctic Mining Pollution-Affected Peatlands Near Yellowknife, Northwest Territories, Jeremy Leathers

Theses and Dissertations (Comprehensive)

Arsenic (As) is a pollutant of global concern that is detrimental to human and environmental health. Between 1948 and 2004, mining operations near Yellowknife, NT released over 20,000 tonnes of As trioxide (As₂O₃) that continues to persist in the surrounding landscape. Although much effort has been put into studying the chemical forms, spatial distribution, ecological impacts, and environmental cycling of As in the area, more work is needed to determine the controls of As mobility between the terrestrial and aquatic components of the landscape. Soils are known reservoirs of legacy As that can release it downslope …

Incorporating Effects-Based Approaches Into Environmental Impact Assessment To Improve Post-Development Monitoring, Carolyn J M Brown

Theses and Dissertations (Comprehensive)

Over the last 50 years, improvements in design of industrial facilities have significantly reduced environmental impacts. But impacts still occur and monitoring programs are the main mechanism to inform when modification/implementation of mitigation is needed. Informed decisions require adequate baseline (pre-development) data to predict impacts based on the development’s design and to understand when the post-development environment has changed. An adaptive monitoring plan provides an effective way to evaluate monitoring results and allow for proactive responses to environmental change before impacts become difficult or challenging to reverse. Unfortunately, baseline data gathered during an environmental impact assessment (EIA) is often inadequate …

Examining Factors Related To Access To Rigorous High School Physics For Black Males: Evidence From The High School Longitudinal Study Of 2009, Jennifer Dacosta

CGU Theses & Dissertations

In the landscape of American education, Black male students face significant barriers in accessing advanced science courses, a challenge that underscores broader issues of equity and inclusion. This study investigated the factors influencing Black male high school students’ access to earn physics credits, focusing on the interplay between school offerings, academic prerequisites, counselor support, personal efficacy in science, and socioeconomic status. Through a detailed analysis of data from the High School Longitudinal Study of 2009, the research adopted a quantitative approach to examine how these variables collectively impact the educational trajectory of these students through multiple regression models which produced …

Evaluation Of Imputation Methods Focusing On Categorical Outcomes, Nadia Bernardo Mendoza

CGU Theses & Dissertations

In general, standard statistical analysis models typically rely on completely observed cases, excluding incomplete rows from the dataset. This approach poses particular challenges when the objective is to predict a rare outcome, especially when some of the ob servations with the rare outcome are incomplete. In such cases, the available information to support the model in predicting this event is reduces. Theoretically correct models may pre dict all instances in the majority class achieving high accuracy, but fail in predicting the rare cases, which are often the most interesting ones. Therefore, it is crucial to make the most of all …

The Specter Of Representation: Computational Images And Algorithmic Capitalism, Samine Joudat

CGU Theses & Dissertations

The processes of computation and automation that produce digitized objects have displaced the concept of an image once conceived through optical devices such as a photographic plate or a camera mirror that were invented to accommodate the human eye. Computational images exist as information within networks mediated by machines. They are increasingly less about what art history understands as representation or photography considers indexing and more an operational product of data processing.

Through genealogical, theoretical, and practice-based investigation, this dissertation project traces a lineage of computation through images from early cybernetics to contemporary machine learning under algorithmic capitalist conditions of …

Autonomous Shuttle Car Docking To A Continuous Miner Using Rgb-Depth Imagery, Sky Rose

Theses and Dissertations--Mining Engineering

A great deal of research is currently being conducted in automating mining equipment to improve worker health and safety and increase mine productivity. Significant progress has been made in some applications, e.g., autonomous haul trucks for surface mining. However, little progress has been made in autonomous face haulage in underground room-and pillar coal mines. Accordingly, this thesis addresses automating the operation of a shuttle car, focusing on positioning the shuttle car under the continuous miner coal-discharge conveyor during cutting and loading operations. The approach uses a stereo depth camera as the sensor, and machine-learning algorithms are used to identify various …

A Gold Mine: The Importance Of Information And Communication Technology (Ict) On Bank Liquidity In Asia And The Pacific, Sarmila Udin, Imbarine Bujang, Nancy Chiuh Noemi

ASEAN Journal on Science and Technology for Development

Financial systems are the entities in charge of promoting, growing, and enhancing economic growth and development. To be viable in the market, financial institutions must maintain enough liquid assets to meet any unforeseen demand from customers at any time needed. Currently, banks are pursuing cutting-edge technologies to survive and thrive in an ever-changing market environment. This paper aims to examine the relationship between information and communication technology (ICT), macroeconomics and bank liquidity risk in Asia and the Pacific. The research took place between 2012 and 2018 and the nations were chosen based on data availability; as a result, the sample …

The Perspective Of Cash Flow Risks On Earnings Measurement, Daisuke Suzuki, Junpei Yamada, Shoji Kamimura

ASEAN Journal on Science and Technology for Development

The essence of earnings in financial statements is significantly influenced by changes in the economic environment. The main objective of this paper is to elucidate a universal principle capable of explaining any types of earnings measurements. To achieve this, we examine the factors influencing earnings by modeling them from a cash flow perspective. Consequently, this paper directs the attention away from stocks and flows, placing emphasis on the risks inherent in income and expenditure in the context of earnings measurements. It highlights the crucial role of these risks in earnings. Additionally, we illustrate that adjusting these risk tolerances enables the …

Social Media Marketing Audiences And Adaptive Behavior In Brunei: Sem Analysis Using Smartpls, Shahid Anjum, Asmah Ahmad, Jefri Basiuni, Najeeba Tazeen

ASEAN Journal on Science and Technology for Development

The social media and Internet technology penetrations and usage are quite high in Brunei Darussalam. The use of social media marketing among micro, small, and relatively medium businesses to promote their products has also grown as businesses desire to engage and build relationships with customers through social media. This has generated an interest in studying the adaption of social media marketing campaigns among customers, which indirectly determines the effectiveness of social media marketing itself, as well as in studying the facilitation factors for such an adaption. Technology Acceptance Model (TAM) has been used extensively because of its simplicity and usefulness. …

Does The Foreign Direct Investment In Emerging Asian Countries Get ‘Greased’ Or ‘Sanded’ By Corruption? Evidence From Gets Model, Rainah Ginsad, Imbarine Bujang, Abdul Aziz Karia, Emelia Girau, Siti Rahayu Beli

ASEAN Journal on Science and Technology for Development

Inflows of foreign direct investment (FDI) considerably boost industrialization and economic growth in emerging economies. Corruption, human capital, and the economic environment are just a few factors mentioned in the literature as influencing FDI inflow. The impact of corruption on FDI, whether FDI is greased or sanded by corruption, has received greater interest in recent empirical study. This study analysed the impact of the Corruption Perception Index (CPI) on foreign direct investment (FDI) in selected Asian emerging economies. Utilising annual panel data covering 22 selected Asian emerging economies, this study uses the General-to-specific (GETS) model to analyse the impact. The …

The Contribution Of Outcome Expectation In Water Saving Among Malaysians For Sustainable Living Standard, Ganesh. R, Vxynette Fiorna, Ammar Abdulaziz Al-Talib, Haslinda. A, Elango Natarajan

ASEAN Journal on Science and Technology for Development

Saving water is an essential component of a higher level of living for each individual in any Nation. The current and next generation will be greatly impacted by attitudes and emotional aspects of social cognitive behaviour. This empirical investigation was carried out in Malaysia. To determine their attitude and behaviour, a convenience sampling method was applied to a sample size of 265 individuals. It was discovered that outcome expectancy significantly improves water saving. Observed self-efficacy, personal elements, and environmental elements all impacted the outcome expectancy. The model evaluation showed that the adjusted R2 was 0.78, or about 78% of the …

Understanding Data Through The Lens Of Topology, Quang Truong

Dartmouth College Master’s Theses

Machine learning depends on the ability to learn insightful representations from data. Topology of data offers a rich source of information for constructing such representations, yet its potential remains under-explored by the broader machine learning community. This work investigates the power of applied topology through two complementary projects: Topological Message Passing with Path Complexes and Persistent Homology for Anomaly Detection. In the first project, we extend the topological message passing framework by introducing a novel approach centered on path complexes, where paths form the fundamental building blocks. Our theoretical analysis demonstrates that this model generalizes existing topological deep learning and …

Multimodal Fusion For Audio-Image And Video Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar

Research outputs 2022 to 2026

Multimodal Human Action Recognition (MHAR) is an important research topic in computer vision and event recognition fields. In this work, we address the problem of MHAR by developing a novel audio-image and video fusion-based deep learning framework that we call Multimodal Audio-Image and Video Action Recognizer (MAiVAR). We extract temporal information using image representations of audio signals and spatial information from video modality with the help of Convolutional Neutral Networks (CNN)-based feature extractors and fuse these features to recognize respective action classes. We apply a high-level weights assignment algorithm for improving audio-visual interaction and convergence. This proposed fusion-based framework utilizes …

Economic Material For Large-Scale H2 Storage And H2-Co2 Separation, Hussein R. Abid, Alireza Keshavarz, Header Jaffer, Basim K. Nile, Stefan Iglauer

Research outputs 2022 to 2026

Hydrogen is a clean fuel that can potentially completely decarbonize the energy supply chain and mitigate global warming. Hydrogen – a highly volatile gas – however, needs to be separated from CO2 during H2 production, and also from cushion gas in H2 geo-storage projects; in addition, large-scale H2 storage is a key obstacle. We thus tested and chemically upgraded common sub-bituminous coal as a material for H2-CO2 separation and H2 storage. The coal adsorbed significant amounts of H2 and CO2 and demonstrated an excellent H2-CO2 separation efficiency if chemically modified. The work presented here thus provides fundamental data required for …

The Impact Of Environmental Policy On Renewable Energy Innovation: A Systematic Literature Review And Research Directions, Hiva Rastegar, Gabriel Eweje, Aymen Sajjad

Research outputs 2022 to 2026

Renewable energy innovations are imperative to tackle the climate change crisis. However, there is a gap in the literature regarding the effectiveness of environmental policies in promoting renewable energy innovations. To bridge this gap, we have adopted a systematic literature review process covering the period from 2005 to 2023. We identified and analysed 29 articles in our final sample. Further, we employ two levels of analysis (individual-policy and policy-mix levels) for analysing the extant research. Our findings show that fiscal incentives and emissions trading policies such as the European Union (EU) Emissions Trading System (ETS) consistently promote renewable energy innovations. …

Understanding The Impact Of Environmental Impact Assessment Research On Policy And Practice, Angus Morrison-Saunders, Annette Nykiel, Nicole Atkins

Research outputs 2022 to 2026

There is an enormous and ever-growing body of environmental impact assessment (EIA) research, much of which is grounded in practice or seeks to advance it. In this paper we show how the impact of EIA research on policy and practice might be conceptualised and how to set about evidencing it. A framework is developed through literature review to account for impact in four areas pertaining to instrumental impact, conceptual impact, capacity building and knowledge brokerage and co-production. Methods for implementing the framework include citations within policy documents along with content analysis to determine influence and interviews or surveys with policy …

Unleashing The Power Of Internet Of Things And Blockchain: A Comprehensive Analysis And Future Directions, Abderahman Rejeb, Karim Rejeb, Andrea Appolloni, Sandeep Jagtap, Mohammad Iranmanesh, Salem Alghamdi, Yaser Alhasawi, Yasanur Kayikci

Research outputs 2022 to 2026

As the fusion of the Internet of Things (IoT) and blockchain technology advances, it is increasingly shaping diverse fields. The potential of this convergence to fortify security, enhance privacy, and streamline operations has ignited considerable academic interest, resulting in an impressive body of literature. However, there is a noticeable scarcity of studies employing Latent Dirichlet Allocation (LDA) to dissect and categorize this field. This review paper endeavours to bridge this gap by meticulously analysing a dataset of 4455 journal articles drawn solely from the Scopus database, cantered around IoT and blockchain applications. Utilizing LDA, we have extracted 14 distinct topics …

Analysis Of Element Yield, Bacterial Community Structure And The Impact Of Carbon Sources For Bioleaching Rare Earth Elements From High Grade Monazite, Melissa K. Corbett, April Gifford, Nick Fimognari, Elizabeth L. J. Watkin

Research outputs 2022 to 2026

Rare earth element (REE) recovery from waste streams, mine tailings or recyclable components using bioleaching is gaining traction due to the shortage and security of REE supply as well as the environmental problems that occur from processing and refining. Four heterotrophic microbial species with known phosphate solubilizing capabilities were evaluated for their ability to leach REE from a high-grade monazite when provided with either galactose, fructose or maltose. Supplying fructose resulted in the greatest amount of REE leached from the ore due to the largest amount of organic acid produced. Gluconic acid was the dominant organic acid identified produced by …