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2024

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Articles 8041 - 8047 of 8047

Full-Text Articles in Physical Sciences and Mathematics

Microbes Of Biotechnological Importance In Acidic Saline Lakes In The Yilgarn Craton, Western Australia, Katelyn Boase, Talitha Santini, Elizabeth Watkin Jan 2024

Microbes Of Biotechnological Importance In Acidic Saline Lakes In The Yilgarn Craton, Western Australia, Katelyn Boase, Talitha Santini, Elizabeth Watkin

Research outputs 2022 to 2026

Acidic salt lakes are environments that harbor an array of biologically challenging conditions. Through 16S rRNA, 18S rRNA, and ITS amplicon sequencing of eight such lakes across the Yilgarn Craton of Western Australia, we aim to understand the microbial ecology of these lakes with a focus on iron- and sulfur-oxidizing and reducing microorganisms that have theoretical application in biomining industries. In spite of the biological challenges to life in these lakes, the microbial communities were highly diverse. Redundancy analysis of soil samples revealed sulfur, ammonium, organic carbon, and potassium were significant diversities of the microbial community composition. The most abundant …


Developing A Novel Ontology For Cybersecurity In Internet Of Medical Things-Enabled Remote Patient Monitoring, Kulsoom S. Bughio, David M. Cook, Syed A. A. Shah Jan 2024

Developing A Novel Ontology For Cybersecurity In Internet Of Medical Things-Enabled Remote Patient Monitoring, Kulsoom S. Bughio, David M. Cook, Syed A. A. Shah

Research outputs 2022 to 2026

IoT has seen remarkable growth, particularly in healthcare, leading to the rise of IoMT. IoMT integrates medical devices for real-time data analysis and transmission but faces challenges in data security and interoperability. This research identifies a significant gap in the existing literature regarding a comprehensive ontology for vulnerabilities in medical IoT devices. This paper proposes a fundamental domain ontology named MIoT (Medical Internet of Things) ontology, focusing on cybersecurity in IoMT (Internet of Medical Things), particularly in remote patient monitoring settings. This research will refer to similar-looking acronyms, IoMT and MIoT ontology. It is important to distinguish between the two. …


A Systematic Review Of K-12 Cybersecurity Education Around The World, Ahmed Ibrahim, Marnie Mckee, Leslie F. Sikos, Nicola F. Johnson Jan 2024

A Systematic Review Of K-12 Cybersecurity Education Around The World, Ahmed Ibrahim, Marnie Mckee, Leslie F. Sikos, Nicola F. Johnson

Research outputs 2022 to 2026

This paper presents a systematic review of K-12 cybersecurity education literature from around the world. 24 academic papers dated from 2013-2023 were eligible for inclusion in the literature established within the research protocol. An additional 19 gray literature sources comprised the total. A range of recurring common topics deemed as aspects of cybersecurity behavior or practice were identified. A variety of cybersecurity competencies and skills are needed for K-12 students to apply their knowledge. As may be expected to be the case with interdisciplinary fields, studies are inherently unclear in the use of their terminology, and this is compounded in …


A Technical Perspective On Integrating Artificial Intelligence To Solid-State Welding, Sambath Yaknesh, Natarajan Rajamurugu, Prakash K. Babu, Saravanakumar Subramaniyan, Sher A. Khan, C. Ahamed Saleel, Mohammad Nur-E-Alam, Manzoore E. M. Soudagar Jan 2024

A Technical Perspective On Integrating Artificial Intelligence To Solid-State Welding, Sambath Yaknesh, Natarajan Rajamurugu, Prakash K. Babu, Saravanakumar Subramaniyan, Sher A. Khan, C. Ahamed Saleel, Mohammad Nur-E-Alam, Manzoore E. M. Soudagar

Research outputs 2022 to 2026

The implementation of artificial intelligence (AI) techniques in industrial applications, especially solid-state welding (SSW), has transformed modeling, optimization, forecasting, and controlling sophisticated systems. SSW is a better method for joining due to the least melting of material thus maintaining Nugget region integrity. This study investigates thoroughly how AI-based predictions have impacted SSW by looking at methods like Artificial Neural Networks (ANN), Fuzzy Logic (FL), Machine Learning (ML), Meta-Heuristic Algorithms, and Hybrid Methods (HM) as applied to Friction Stir Welding (FSW), Ultrasonic Welding (UW), and Diffusion Bonding (DB). Studies on Diffusion Bonding reveal that ANN and Generic Algorithms can predict outcomes …


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 Jan 2024

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 …


Gans And Synthetic Financial Data: Calculating Var*, David E. Allen, Leonard Mushunje, Shelton Peiris Jan 2024

Gans And Synthetic Financial Data: Calculating Var*, David E. Allen, Leonard Mushunje, Shelton Peiris

Research outputs 2022 to 2026

Generative Adversarial Neural nets (GANs) are a new branch of machine learning techniques. A GAN learns to generate new data from the training data set. We examine the characteristics of the fake financial data using GANs trained on samples of daily S&P 500 and FTSE 100 index values. GANs feature two competing neural networks in a game theoretic context. The Generator net generates pseudo data that is presented to the discriminator net which then attempts to distinguish between the real and the fake data. This facilitates unsupervised learning on the dataset. The generative network generates data sets, while the discriminative …


Secrecy Rate Maximization For Active Reconfigurable Intelligent Surface Assisted Mimo Systems, Bin Gao, Jingru Zhao, Shihao Yan, Shaozhang Xiao Jan 2024

Secrecy Rate Maximization For Active Reconfigurable Intelligent Surface Assisted Mimo Systems, Bin Gao, Jingru Zhao, Shihao Yan, Shaozhang Xiao

Research outputs 2022 to 2026

Reconfigurable intelligent surface (RIS) is a promising technology for future 6G communications and has been used to enhance secrecy performance. However, the performance improvement is restricted by the 'double fading' effect of the reflection channel link. To address this issue, we introduce an active RIS design, where the reflecting elements of RIS not only adjust the phase shift but also amplify the reflected signal through the amplifier integrated into its elements. To obtain a satisfactory solution to the non-convex problem resulting from this design, the penalty dual decomposition based alternating gradient projection (PDDAPG) method is proposed. We compare the proposed …